informing the design of a smartphone-based telemonitoring … › bitstream › 1807 › 72803 ›...

Informing the Design of a Smartphone-Based Telemonitoring System for Multiple Chronic Conditions

by

Mehwish Sultan

A thesis submitted in conformity with the requirements for the degree of Master of Health Science in Clinical Engineering

Graduate Department of IBBME University of Toronto

© Copyright by Mehwish Sultan 2016

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Informing the Design of a Smartphone-Based Monitoring System

for Multiple Chronic Conditions

Mehwish Sultan

Master of Health Science in Clinical Engineering

Graduate Department of IBBME University of Toronto

2016

Abstract

People with multiple chronic conditions (MCC) often struggle with managing the diverse facets

of their health, which includes monitoring physiological parameters such as blood pressure and

weight, maintaining appropriate diet and level of exercise, adhering to medications, keeping

updated health records and traveling to multiple healthcare providers. Therefore a user-centric

design process was utilized to design a smartphone-based telemonitoring system to support self-

care and clinical management of patients with MCC. Semi-structured interviews with fifteen

patients and eleven clinicians and an analysis of existing disease-specific smartphone

applications provided insight into the requirements and architecture for designing the

telemonitoring system for MCC. Utilizing the gathered information, prototypes of smartphone

application were created and refined through three rounds of usability testing. Themes and

design principles generated in this study highlighted the complexity and challenges for designing

interventions for multiple conditions, and could be utilized for informing the design of

smartphone based telemonitoring systems for MCC patient populations.

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Acknowledgments

This project would not have been possible without the invaluable support, guidance and

contributions of many individuals.

First and foremost, I would like to thank all members of my committee. I offer my deep gratitude

to my supervisor, Dr. Emily Seto who has provided me with guidance throughout my thesis,

even from afar. You challenged my thinking by helping me question assumptions and view

issues from multiple perspectives. To Dr. Joe Cafazzo, your advice was of immense value in

guiding the design and was greatly appreciated. Dr. Warren McIsaac, thank you so much for

your continuous support with patient and physician recruitment. Dr. Sandy Logan, your clinical

advice was greatly appreciated and much valued. I owe a debt of gratitude to Dr. Kerry Kuluski

for her time and careful attention to detail. Each of you has given your time and expertise and

for that I am very grateful.

I would like to say a big thank you to the team at the Centre for Global eHealth Innovation:

Melanie, Marvin, Anson, Justin, Dave, Akib, Shivani, Romina, Deanna and the list goes on.

Marvin, Anson and Justin, the development of the project would not have been possible without

you. Thank you for staying and spending countless hours to hatch through the challenges.

I would also like to thank Dr. Andrew Sparrow, Soumia and members at the Family Health

Teams of UHN and Mount Sinai for participating in my study and/or continuously helping me

with participant recruitment over the past 2 years. I would also like to acknowledge the help of

Dr. Gary Lewis and Nasil for speeding up the last phase of my study. My gratitude also goes out

to the patients who participated in my study and provided insightful feedback for the project.

Finally, thank you to my parents, Sultan and Shabana, for supporting and loving me endlessly

through the years, and to my two brothers, Saad and Shams, who have been putting up with me

from the very beginning. Last but not least, thank you to Abid for being the voice of reason at all

times and pushing me in the right direction – and of course for relentlessly sending flowers to the

center.

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Table of Contents

Table of Contents

Acknowledgments .............................................................................................................................................. iii

Table of Contents ................................................................................................................................................ iv

List of Tables ....................................................................................................................................................... vii

List of Figures .................................................................................................................................................... viii

List of Abbreviations ......................................................................................................................................... ix

Introduction ................................................................................................................................................... 1 1

1.1 Problem Statement and Rationale .......................................................................................................................... 1 1.2 Objectives ........................................................................................................................................................................... 2 1.3 Research Questions ........................................................................................................................................................ 3

Background .................................................................................................................................................... 4 2

2.1 Prevalence of Multiple Chronic Conditions .......................................................................................................... 4 2.2 Self-‐Management of Chronic Conditions .............................................................................................................. 6 2.3 Telemonitoring for Chronic Conditions ................................................................................................................. 8 2.3.1 Patients with Heart Failure .......................................................................................................................... 9 2.3.2 Patients with Chronic Obstructive Pulmonary Disease ............................................................... 10 2.3.3 Patients with Chronic Kidney Disease ................................................................................................. 11 2.3.4 Patients with Diabetes Mellitus .............................................................................................................. 12 2.3.5 Patients with Hypertension ...................................................................................................................... 14 2.3.6 Patients with Multiple Chronic Conditions ........................................................................................ 15

2.4 Leveraging Existing Technology ........................................................................................................................... 17

Methods ......................................................................................................................................................... 19 3

3.1 Participant Recruitment ........................................................................................................................................... 20 3.1.1 Patient Recruitment ..................................................................................................................................... 20 3.1.2 Clinician Recruitment .................................................................................................................................. 21

3.2 Data Collection and Analysis .................................................................................................................................. 21 3.2.1 Phase I: Requirements Gathering through Formative Interviews ........................................... 21 3.2.2 Phase II: Leveraging Existing Applications to Design Prototypes ........................................... 24 3.2.3 Phase III: Iterative Usability Testing .................................................................................................... 24

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Results ............................................................................................................................................................ 28 4

4.1 Phase I: Requirements Gathering using Formative Interviews ............................................................... 28 4.1.1 Participant Characteristics ....................................................................................................................... 28 4.1.2 Themes Generated from Interviews with Patients and Clinicians .......................................... 31

4.2 Phase II: Smartphone Application Design and Architecture .................................................................... 53 4.2.1 Comparison of Existing Apps ................................................................................................................... 53 4.2.2 Design Principles ........................................................................................................................................... 61

4.3 Usability Testing Round #1 ..................................................................................................................................... 62 4.3.1 Scenarios and Prototype Designs ........................................................................................................... 62 4.3.2 Participant Characteristics ....................................................................................................................... 63 4.3.3 Results from Usability Testing Round #1 ........................................................................................... 65



Discussion .................................................................................................................................................. 103 5

5.1 Difficulties in Patient Recruitment ..................................................................................................................... 104 5.2 Module to Assist Behavior Change ..................................................................................................................... 105 5.3 “One-‐size-‐does not fit all” level of severities ................................................................................................... 108 5.4 Disease-‐Specific or Reading-‐Specific Intervention ...................................................................................... 110 5.5 Implementation of Telemonitoring System .................................................................................................... 111 5.6 Strengths and Limitations ..................................................................................................................................... 113

Conclusions and Future Work ............................................................................................................. 115 6

Bibliography ..................................................................................................................................................... 117

Appendices ........................................................................................................................................................ 129 Appendix A – Sample of Designs ......................................................................................................................... 129 Appendix B – Pre-‐Study Questionnaires ......................................................................................................... 134 Appendix C – Post-‐Study Questionnaires ....................................................................................................... 136 Appendix D – Clinician Interview Guide .......................................................................................................... 138

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Appendix E – Patient Interview Guide ............................................................................................................. 140 Appendix F – Product Requirements ................................................................................................................ 144 Appendix G – Feature Files .................................................................................................................................... 150 Appendix H – Summary of Alerts Algorithms ............................................................................................... 156 Appendix I – Verification Test .............................................................................................................................. 158

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List of Tables Table 1: Patient demographics for semi-‐structured interviews. 29 Table 2: Technology-‐related characteristics of patients in the semi-‐structured interviews. 30 Table 3: Summary of themes, subthemes and corresponding features. 31 Table 4: Comparison of features of existing disease-‐specific apps. 54 Table 5: Comparison of symptoms questions in disease-‐specific smartphone applications. 55 Table 6: Scrollable trend review page content for blood pressure. 57 Table 7: Comparison of existing smartphone applications and issues that needed to be resolved. 59 Table 8: Findings and resultant design principles. 61 Table 9: Patient demographics for Usability Testing Round 1. 64 Table 10: Patients’ technology-‐related characteristics for Usability Testing Round 1. 64 Table 11: Patient demographics for Usability Testing Round 2. 73 Table 12: Patient technology-‐related characteristics for Usability Testing Round 2. 74 Table 13: Symptoms questions for hypertensive patients [87]. 82 Table 14: Different ranges for blood sugar during usability testing. 87 Table 15: Patient demographics for Usability Testing Round 3. 89 Table 16: Patients’ technology-‐related characteristics for Usability Testing Round 3. 89 Table 17: User responses to usability questions in the post-‐study questionnaire for Usability 91

Testing Round 3.

Table 18: User responses about the visuals from the post-‐study questionnaire for Usability 91

Testing Round 3

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List of Figures Figure 1: Proportion of Medicare beneficiaries with combinations of chronic conditions [2]. 5 Figure 2: Chronic conditions to be encompassed into the MCC smartphone platform. 9 Figure 3: Architecture of Medly system [77]. 18 Figure 4: Blood pressure trend review algorithm utilizing 70% rule. 57 Figure 5: Screenshots from 1st set of designs of MCC app used in Usability Testing Round 1. 62 Figure 6: Screenshots from 2nd set of designs of MCC app used in Usability Testing Round 1. 63 Figure 7: Screenshots from prototype of MCC app used in Usability Testing Round 2. 72 Figure 8: Blood pressure instructions page. 80 Figure 9: Feedback given after first blood pressure reading. 83 Figure 10: Overall action taking into account first and second readings. 83 Figure 11: Updated version of first blood pressure reading page. 84 Figure 12: Updated version of blood pressure feedback page. 84 Figure 13: Older version of blood glucose page. 86 Figure 14: Updated version of blood glucose page. 86 Figure 15: Main page of the guided wizard on the MCC app. 92 Figure 16: Instructions page that allows user to temporarily skip taking a measurement. 92 Figure 17: Screen to guide users to complete unfinished tasks. 94 Figure 18: Readings page on MCC app. 96 Figure 19: Blood glucose log page. 96 Figure 20: Blood pressure log page. 98 Figure 21: Trend information page. 98 Figure 22: Current display of measured reading in MCC app with respect target range. 102 Figure 23: May 2015 design aimed to use sliding marker to provide context for measured reading. 102 Figure 24: Chronic disease risk factors are common to many conditions [24]. 106 Figure 25: Components of the main page of MCC app wireframe in default mode. 129 Figure 26: Main page of the MCC app wireframe after measurements have been recorded. 129 Figure 27: Wireframe for timeline of events. It contains a history of alerts and major events. 129 Figure 28: Details page pertaining to the parameter, blood glucose. 129 Figure 29: November 2014 checklist format. 131 Figure 30: December 2014 checklist format. 131 Figure 31: February 2015 checklist format. 131 Figure 32: March 2015 checklist format in grid view. 131

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List of Abbreviations

CCM – Chronic Care Model

CDPM - Chronic Disease Prevention and Management

CIHI – Canadian Institute of Health Information

CKD – Chronic Kidney Disease

COPD – Chronic Obstructive Pulmonary Disease

DM – Diabetes Mellitus

ECCM – Expanded Chronic Care Model

EPR – Electronic Patient Record

FHT – Family Health Team

HBM – Health Belief Model

HF – Heart Failure

HTN – Hypertension

ICT - Information and Communication Technologies

MSH – Mount Sinai Hospital

NYGH – North York General Hospital

PHIT – Personal Health Information Team

REB – Research Ethics Board

RCT – Randomized Controlled Trial

TWH – Toronto Western Hospital

TGH – Toronto General Hospital

UHN – University Health Network

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Introduction 1

1.1 Problem Statement and Rationale

Continued advances in science and technology, as well as improvements in environmental and

social conditions have contributed to increased life expectancy around the world [1]. However,

greater life expectancy has resulted in a rising number of individuals with chronic diseases [1].

Chronic diseases are “conditions that last a year or more and require ongoing medical attention

and/or limit activities of daily living” [2]. This includes arthritis, chronic respiratory problems,

diabetes, heart diseases, and hypertension, among others [2]. High prevalence of chronic diseases

has led to yet another phenomenon – growing number of people with multiple chronic conditions

(MCC), which is the co-existence of two or more diseases [3] [4]. Prevalence of multiple chronic

diseases increases with age [4]. It is estimated that more than half (56%) of seniors – e.g. people

aged 65 or older – have two or more chronic conditions [5].

People with multiple chronic conditions have complex health needs, and therefore require the use

of more health services. Studies show that seniors with three or more chronic conditions have

nearly three times the number of healthcare visits than seniors with no reported comorbidities

[3]. These healthcare visits include trips to the family doctor, specialists, nurses, pharmacists,

dieticians, physiotherapists, and social workers, and henceforth the financial impact for

addressing multiple chronic conditions is immense [3]. In Canada, seniors with multiple chronic

conditions account for 40% of healthcare use among seniors, even though they comprise only

24% of the senior population [3]. Similarly, 66% of total healthcare spending gets directed

towards the care of 27% of Americans with multiple chronic conditions [6]. With increasing

numbers of chronically ill patients and limited availability of resources to manage them, the

health care system’s ability to provide efficient and effective service will be continuously

challenged with time [1]. It is therefore imperative to identify and promote alternatives to

conventional patient management that would perform appropriate monitoring and treatment of

patients while reducing costs.

One way of addressing the issue is through home telemonitoring technology, which collects

monitoring information (e.g. blood pressure and weight), gives patients access to their own data,

supports self-management and may reduce the need for home visits and ultimately the cost of

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homecare [7]. Many tools are being developed for self-management of chronic conditions and

there is a growing body of research on the effectiveness of telemonitoring interventions for

chronic conditions [8][9]. However, they are often stand-alone solutions geared towards the

management of a single chronic disease, such as diabetes, depression and asthma [10]. Patients

with multiple chronic conditions have more complex needs, they have a higher risk of

medication issues and they often receive conflicting clinical advice, which hinders their ability to

self-manage their conditions effectively [11].

1.2 Objectives

One area of research in telemonitoring consists of patients using the mobile phone for conducting

self-management, combined with the use of technology such as Bluetooth-enabled medical

devices that collect vital signs while patients reside at home. Such technologies allow patients to

be involved in collecting information on their personal clinical parameters, and aids in clinical-

decision making for both healthcare providers and patients [12].

Therefore, the first objective of this project was to identify the needs of patients and clinicians

with regards to the management of multiple chronic conditions and determine how those needs

would translate into features. The second objective was to develop design principles in order to

implement the identified features. The third objective was to refine and test the smartphone

application through usability testing.

Existing smartphone applications based on singular conditions were leveraged to develop the

prototype. The MCC smartphone application aimed to provide a self-management tool for

patients with combinations of two or more of the following conditions: heart failure (HF),

chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), diabetes mellitus

(DM) and hypertension (HTN). Due to time constraints and difficulties in patient recruitment,

the final designs of the smartphone application were focused on chronic conditions that were

most frequently observed among the patients recruited in the study: DM and HTN.

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1.3 Research Questions

Qualitative analysis of semi-structured interviews and iterative usability testing with patients and

clinicians were used to answer the following research questions:

Phase I – Semi-structured Interviews

• What are the needs of MCC patients for self-care?

• What are the needs of the clinicians when providing care for MCC patients?

• How do these needs translate into features?

Phase II – Designing a Prototype

• What are the design principles to develop a smartphone-based tool for self-management

of MCC?

Phase III – Usability Testing

• How do you optimize the features of the mobile application for the MCC patient

population?

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Background 2

2.1 Prevalence of Multiple Chronic Conditions

A large number of people are living with multiple chronic conditions. For example, hypertension

is the most commonly reported chronic condition among Canadian seniors (47%, estimated 2

million seniors), and an analysis of five clinical trials of hypertensive patients in Canada revealed

that 89% to 100% of the hypertensive patients had multiple chronic conditions [3][4]. According

to Canadian Institute of Health Information (CIHI), after hypertension and arthritis (14%), the

next most common combination of chronic conditions among seniors was hypertension and heart

disease (12%), followed by hypertension and diabetes (11%), heart disease and arthritis (6%) and

hypertension and cancer (6%) [3]. Chronic obstructive pulmonary disease (COPD) was the least

common chronic condition reported among those included in the CIHI study (4%, estimated

190,000 seniors), but it has been reported to be one of the leading causes of hospital admissions

in Canada [3][13].

A recent study examined the prevalence of co-occurrence of two or more conditions in Ontario

and found that there was a great diversity in the combination of chronic conditions [14]. Diabetes

and hypertension (9%) was among the top five common clusters for individuals with two

conditions. Among individuals with three conditions, hypertension and arthritis existed in all top

five clusters, in combination with diabetes (10.9%), depression (6.8%), cancer (5.8%), coronary

syndrome (5%), and asthma (4.9%). The researchers [14] also investigated the patterns of co-

occurring conditions for individuals with four and five chronic conditions but found no dominant

patterns, with the combination of coronary syndrome, diabetes, hypertension and arthritis (5.6%)

being the highest prevalence. However, it should be noted that although 5% sounds insignificant,

it refers to 650,000 individuals of the total estimated 13 million individuals included in the study

[14].

A study [2] of Medicare beneficiaries in the United States found that 50% of the beneficiaries

were receiving care for one or more chronic conditions and the average payment per beneficiary

increased dramatically as the number of chronic conditions increased. The study examined six

most common conditions (shown in Figure 1) and observed high prevalence of multiple chronic

conditions when cross-examining the existence of other concurrent conditions among the

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beneficiaries. Diabetes was the most prevalent singular chronic condition observed. Nearly 33%

of the beneficiaries with chronic kidney disease (CKD) had one other condition and almost 50%

of them had two or more conditions. For COPD, approximately 33% had one other condition and

39% had two or more other conditions. Among individuals with HF, almost 73% of them had

one or more other chronic conditions. The most common combination of conditions occurring

together was HF and CKD (52.9%), followed by diabetes and CKD (51%) [2]. Study by Sinnige

et al. [11] also indicated that patients with CKD often have other coexisting chronic conditions

such as diabetes and cardiovascular diseases, which would include HF. Hypertension was not

one of the conditions included in that study, but data such as this confirms that there is a high

prevalence of multiple chronic conditions.

Figure 1: Proportion of Medicare beneficiaries with combinations of chronic conditions (Figure was adapted

from Schneider et al. [2]).

Multiple studies have reported prevalence rates for different combinations of two or more

chronic conditions [11] [15]. Close examination of the prevalence reported per study would

denote that there are no significantly dominant combinations of chronic conditions, because

many of the prevalence percentages are below 15% [14] [11] [15]. However, despite the lack of a

dominant percentage, these studies help shed light on the most commonly observed

combinations among the different groups of populations [14][11] [15][16]. These studies also

highlight the complexity and challenges that exist for designing interventions for multiple

chronic conditions, because it brings to question whether interventions should be targeting

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specific combinations of common conditions or specific problems that patients with multiple

conditions experience [9].

This thesis explored design principles and features for a smartphone-based system for

management of HF, COPD, CKD, DM and HTN. These five conditions were of particular

interest in the MCC smartphone project because: 1) they are highly prevalent (including in

combinations with each other) or impactful conditions in older adults, 2) they are commonly

targeted in telemonitoring studies and 3) would allow us to build upon the knowledge from the

well-researched, usability tested chronic conditions applications that had already been worked on

at our Centre for Global eHealth Innovation. The high prevalence of these conditions is

supported by multiple studies [3][11] [17].

2.2 Self-Management of Chronic Conditions

Self-management provides a means for the healthcare staff to provide patients with support that

will build patients’ skills and confidence in managing their health conditions, through regular

assessment of progress and problems, goal setting, and problem-solving support [18]. A review

by Clark et al. [19, p.5] states that self-management is interpreted as “day-to-day tasks an

individual must undertake to control or reduce the impact of disease on physical health status.

At-home management tasks and strategies are undertaken with the collaboration and guidance of

the individual’s physician and other health care providers.” The importance of self-management

for people with chronic conditions is increasingly being recognized as a key component of

improving the overall health of patients [20] [21]. There are vast amounts of literature supporting

a shift away from the traditional models of healthcare characterized by active expert(s) and

passive patients towards a model where there is more involvement of patients with the day-to-

day realities of their chronic conditions [22]. There are also multiple articles citing that the

healthcare system needs to be reformed from the current acute-focused care to one that embodies

chronic disease management as well as provides support for self-management among patients,

their caregivers and care providers [23]. It is widely being recognized that the process of

supporting patients towards self-management will require a large role from primary health care

providers. Within Canada, Alberta and British Columbia have developed chronic disease

frameworks that aim to explicitly enhance self-management support for their patients with the

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primary health care team having the central role [20]. The government of Ontario has also taken

steps to improve coordination of care for complex care patients through the establishment of the

Chronic Disease Prevention and Management (CDPM) Framework to support the transformation

of the healthcare system from one that is designed for acute illness to one that will support the

prevention and management of chronic disease [24][25]. The framework is based on the Chronic

Care Model (CCM) developed in the U.S. and the Expanded Chronic Care Model (ECCM)

developed in British Columbia, and enhances the role of primary healthcare as well as the

community. Programs that provide patients with home visits, telephone or individual coaching

by primary care nurses and doctors as well as professionals such as social workers and

pharmacists are emerging to help patients succeed in self-managing. These programs grounded

in self-management are a promising approach for improving health outcomes because they

enable patients to monitor their symptoms and teach them how to prevent and respond to certain

health-related problems [20] [22] [26].

Many health behavior change theories have been emerged over the years based on psychosocial

and behavioral sciences and have been utilized to develop interventions to promote better

management of health [27]. One useful theoretical perspective for understanding disease self-

management derives from the Health Belief Model (HBM). The HBM is a conceptual framework

developed in the 1950s to explain and predict changes in health-related behaviors based on the

attitudes and beliefs of individuals [28]. The constructs of this model summate to the conclusion

that the course of action a person takes depends on the balance between a person’s perceptions

on the threat to their health and effectiveness of a recommended health action. The perceived

threat to the person’s health and well-being is affected by the person feeling susceptible to

contracting an illness (perceived susceptibility) and feeling there will be serious consequences if

their condition worsens (perceived severity). The individual is more likely to take corrective

actions to reduce their risk if they believe the potential benefits (perceived benefits) of taking

actions outweigh the cost or barriers (perceived barriers) to taking corrective actions [28]. The

model also includes a construct called cues to action, which acts as a force to promote the patient

to perform an action, such as a written reminder to oneself to take their medication. The last

construct, self-efficacy, was added into the model in 1988 to account for the fact that patient’s

confidence in their ability to successfully perform actions also affects their decision-making and

behavior. The health belief model was utilized in this study to frame the perceptions of the

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participants and identify barriers and motivational factors that could be utilized in designing a

system for self-management of multiple chronic conditions.

2.3 Telemonitoring for Chronic Conditions

Telemonitoring entails tasks related to handling clinical aspects of chronic condition away from

the hospital or doctor’s office [19]. Telemonitoring through use of audio, video or other

telecommunication technologies to monitor patient status at a distance has emerged as a possible

solution to help care for the increasing population of older adults with chronic conditions.

Several medical trials have been carried out to evaluate the effects of self-monitoring,

supplemented with programs designed by professionals to support patients with health-related

decision-making and increasing their knowledge on how to manage their conditions in everyday

life [29]. These evaluations have assessed the effectiveness of telemonitoring by comparing the

number of hospital admissions and length of stay, bed days of care, emergency department visits,

mortality, quality of life and costs pre- and post- telemonitoring or between telemonitoring group

and control group [18]. Several studies and systematic reviews have demonstrated that

telemonitoring interventions for management of chronic health conditions such as diabetes,

hypertension, or heart failure can lead to positive health outcomes and reductions in healthcare

costs [8][30]. Nevertheless, there are also contradictory studies that imply that telemonitoring

does not lead to improvements. These contradictory studies have often excluded a self-care

component or the telemonitoring systems were difficult to use [31][32]. Others such as Koehler

et al. [33] have stated that telemedicine management may not be appropriate to use for all

patients because studies such as these targeted patients with a range of severity in their chronic

condition as opposed to targeting patients who were most ill and frequently hospitalized.

There was a limited amount of literature on the effectiveness of telemonitoring of smartphone

applications for MCC. Therefore, before embarking into designing and developing a

telemonitoring intervention for MCC, self-management requirements and effectiveness of

telemonitoring systems was reviewed for the singular chronic conditions that were to be included

into the MCC project: HF, COPD, CKD, DM and HTN (Figure 2). The next section discusses

the literature on the effectiveness of telemonitoring for each of these conditions, and concludes

with a summary of the literature on telemonitoring for MCC.

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Figure 2: Chronic conditions to be encompassed into the MCC smartphone platform.

2.3.1 Patients with Heart Failure

There are an estimated 500,000 Canadians and more than 5 million people in the US living with

heart failure (HF) [22] [23]. The direct and indirect costs of HF in the US are estimated to be

$33.2 billion annually [23]. According to Darkins et al. [24], the Canadian HF readmission rate

between 1997 and 2000 was 23.6% in one year. Patients with HF need close monitoring in order

to detect deterioration of their health condition and to optimize their treatment regimens [27].

However, despite being scheduled for more frequent clinic visits, many HF patients meet with

their HF clinicians only every few months due to factors such as travelling being a difficulty or

financially burdensome, especially for those who live farther away [34]. Multiple studies have

shown that improvement in patient self-management of HF could lead to improved health

outcomes, fewer required clinic visits and overall reduction in healthcare costs [35][36].

However, self-care is difficult for HF patients because early symptoms are subtle and the

treatment regimen is complex, which may lead to HF patients having low self-confidence in their

ability to perform self-care [37] [38]. Therefore, methods to assist patients develop efficient self-

care strategies need to be utilized in order to improve health outcomes and decrease healthcare

costs.

Remote patient monitoring is one method to assist HF patients with management of their

condition. For HF patients, remote monitoring of parameters such as weight, symptoms and

blood pressure at home can be used to generate alerts to care providers when the system detects

deterioration in any of the parameters. The data could additionally be utilized to provide HF

patients with self-care feedback to help them manage their condition more effectively. Large-

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scale RCTs on remote monitoring have also been performed for HF patients and these trials have

also shown notable decreases in the percentage of patients who needed hospital readmissions, as

well as a reduction in length of hospital stay and improved quality of life [39] [40] [41]. Multiple

studies and systematic reviews on remote monitoring or telephone support for HF patients found

improvements in HF patient outcomes as well as reduction in rates of hospitalization, all-cause

mortality and costs [42] [43] [44] [45].

A mobile phone-based remote monitoring system called Medly HF was designed and developed

at the Centre for Global eHealth Innovation to help HF patients with self-management of their

condition. The Medly HF mobile application was developed based on input from the specialists

at the Heart Function Clinic at Toronto General Hospital. Patient’s weight, symptoms and blood

pressure were collected by the patient at home. The data were automatically sent via the mobile

phone to data servers. The collected data were used with a decision support system to guide HF

patients on how to take better of their health and to send alerts to the health care providers when

needed. Findings from a RCT with Medly HF indicated that self-care and clinical management

support from a mobile phone-based telemonitoring system can lead to improved quality of life

and improved health outcomes. Patient adherence to the system was high with the patients

feeling more empowered, less anxious and more aware of their heart failure condition [12].

Components of the Medly HF mobile application were examined in order to assess how HF

management could be integrated into MCC mobile application.

2.3.2 Patients with Chronic Obstructive Pulmonary Disease

Although only four percent of Canadians are diagnosed with Chronic Obstructive Pulmonary

Disease (COPD), it is a leading cause of hospital admissions in Canada [13]. COPD is also the

leading causes of morbidity and mortality around the world, with an estimated 80 million people

worldwide having moderate to severe COPD [46]. The progression of this disease has a large

negative impact on function and quality of life for many patients, and can cause frequent hospital

admissions and increase in healthcare costs [13]. Self-management interventions can help

patients with COPD develop the knowledge and skills to carry out disease-specific medical

regimens and sustain healthy lifestyle behaviors [47]. Rates of COPD-specific hospital

admissions and emergency visits are reduced when education and self-management skills are

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part of the care plan and there is ongoing support available [48]. However, as stated by Bourbeau

et al. [48] it is only after achieving behavior change that self-management of the COPD would

result in better patient outcomes and reduction in utilization of healthcare services.

There is an increase in the number of COPD patients being managed at home to reduce health-

related costs while also facilitating patient’s comfort [49]. Data such as oxygen saturation, vital

signs and symptoms have been used for telemonitoring studies [49]. COPD-specific clinical tools

such as St. George’s Respiratory Questionnaire, the COPD Clinical Questionnaire and Chronic

Respiratory Questionnaire are some lengthy questionnaires to assess patient’s health status based

on information on daily symptoms, activity limitations and other causes for exacerbation of their

disease. However, even short, simple and reliable instruments such as the COPD Assessment

Test with five to seven items for comprehensive daily monitoring of COPD-specific symptoms

can effectively identify COPD exacerbations, guide early intervention and facilitate self-

management [50].

At the Centre for Global eHealth Innovation, a mobile phone-based application has been

previously developed to support patients with self-managing their COPD by providing a tool for

daily monitoring of COPD-specific symptoms and treatments, and support the education of self-

management behaviors over time. The Medly COPD mobile application was created with

clinical input from specialists in the Asthma and Airway Centre at Toronto Western Hospital and

a pilot trial with the mobile application is to be completed in Fall 2015. Components of the

Medly COPD mobile application were examined in order to assess how COPD management

could be integrated into MCC mobile application.

2.3.3 Patients with Chronic Kidney Disease

Chronic kidney disease (CKD) is increasingly recognized as a global public health problem [51].

It is estimated that 1.9 million to 2.3 million of Canadians are affected by CKD [52]. CKD is

defined as the presence of kidney damage or reduced kidney function for more than 3 months,

with the measured or estimated glomerular filtration rate (eGFR) being less than 60mL/min per

1.73m2 or the patient having abnormalities in urine sediment, renal imaging or biopsy results

[52]. Patients with CKD often have other coexisting chronic conditions such as cardiovascular

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disease and diabetes [51]. The direct cost of treating all Canadians with CKD is estimated to be

around $3 billion per year without taking comorbidities into consideration [53].

The progression of kidney disease is slow and happens over a period of years. The development

of CKD has been divided into five stages, based on eGFR, which is based on a math formula

using the person’s age, race, gender and their serum creatinine [54]. At Stage 1, kidney function

is normal and it is minimally reduced by Stage 2. Supporting self-management for patients with

CKD is an important element in slowing down the progression of the disease. Medicines and

lifestyle changes slow down the progression of CKD in the early stages. More monitoring is

required for the later stages of CKD. In a RCT in Taiwan, self-management support and

education provided by a nurse practitioner reinforced by a team from a primary health care clinic

led to a reduction in the progression of CKD and reduction in hospitalization of patients with

Stage 3 and 4 of CKD [55]. In another study, tight control of blood glucose and blood pressure

were found to be essential in improving outcomes, preventing or delaying the progression of

patient condition to Stage 5, which is the most severe or end-stage kidney failure [56].

The science of information and communication technologies (ICT) has matured to an extent that

it is able to provide suitable and reliable means for support of patient self-management and

enables easier integration of disease management into everyday life [57]. The Centre for Global

eHealth Innovation and the Division of Nephrology, Mount Sinai Hospital/University Health

Network developed a mobile phone-based care system for telemonitoring of CKD patients. The

mobile app enables patients to monitor their blood pressure and symptoms, as well as confirm

their medications and view their blood laboratory results. Additionally, alerts and instructions are

sent to patients to promote self-care and to their healthcare provider when necessary.

Components of the CKD application were examined for the purpose of developing an

intervention tool for patients with multiple chronic conditions.

2.3.4 Patients with Diabetes Mellitus

Diabetes mellitus (DM) is one the most prevalent chronic diseases worldwide. It is estimated that

almost 246 million worldwide are diagnosed with diabetes. In Canada, an estimated 3 million

individuals have diabetes, and total yearly costs including secondary complications is $16.9

13

billion a year [58] [59]. Poor management of diabetes increases the chances of developing micro

and macro-vascular complications, whereby these damages to the blood vessels can cause

complications including cardiovascular disease, vision loss, kidney failure and nerve damage

[60].

The self-care demand, which includes lifestyle changes, can overwhelm patients with diabetes

and medication regimens [61]. Additionally, the training that is provided to diabetes patients at

diagnoses is often generic and difficult to apply to real-world settings. Many individuals with

diabetes lack a proper understanding of how each care component contributes to overall

glycemic control and hence non-adherence to recommended care regimens is highly prevalent

[61]. For example, data from a large national study with a sample size of 1,480 patients with type

2 diabetes found that 29% of patients insulin-requiring patients, 65% of those on oral

medications and 80% of those treated with diet alone never monitored their blood glucose or did

so less than once per month [62]. Many patients with insulin-requiring diabetes lack the skills

required for them to manage their condition properly, and therefore they end up with poor

adherence to medication therapy and clinical recommendations for self-monitoring [63]. In one

study [64], some individuals did not see the correlation between increased exercise and better

glycemic control, and therefore they were less motivated to increase their level of physical

activity. This therefore leads to less than half of Type II diabetes patients being able to achieve

optimal levels of HbA1c, the gold standard measure of glycemic control because it reflects

average glycemia over several months and it is strongly correlated with diabetic complications

[64].

Despite the complexity of the care regimen for diabetes, patients with good self-management

behaviors can achieve glycemic control [65]. Routine self-care, the ability to problem-solve and

make decisions based on blood glucose levels can reduce the risk of complications that may arise

overtime [64]. One key component of manage diabetes is self-management training [61].

Considering the increased access to Internet and mobile phones, there is an opportunity for

telemonitoring to be utilized in providing training by enabling the transfer of information and

feedback between patients and clinicians [65].

A recent example of an intervention that achieved behavior change through a mobile system was

a mobile health (mHealth) application named bant that engaged adolescents with type 1 diabetes

14

to carry out self-management activities. The bant application was developed at the Centre for

Global eHealth Innovation. It allowed adolescents to transfer their blood glucose readings

wirelessly from a glucometer into the mobile phone, collect points for taking required blood

glucose measurements and then redeem the points for iTunes rewards. The participants were also

able to view positive and negative trends on their mobile phones. In a 12-week pilot (n = 20)

carried out in 2012, the use of the bant application led to a 49.6% increase in the frequency of

blood glucose measurements [67]. This demonstrated that a properly designed mobile application

could be utilized to engage patients with insulin requiring diabetes and potentially influence

positive behavior changes. Utilizing the features of bant, a Medly Diabetes app was developed at

the Centre for Global eHealth Innovation to support patients with insulin-requiring diabetes in

tracking their data, identify trends and promote healthy behaviors through the use of adherence

mechanisms such as automated notifications and feedback. Components of the Medly Diabetes

application were examined for the purpose of developing the MCC mobile application.

2.3.5 Patients with Hypertension

Hypertension, also known as high blood pressure, is a highly prevalent chronic condition

affecting up to 23% of Canadian adults and nearly one-third of adults in the United States [66]

[67]. Costs attributed to hypertension in Canada were estimated to be $13.9 billion in 2010,

representing 10.2%, a large proportion of the healthcare spending [68]. Hypertension in

association with diabetes is also one of the main factors in causing retinal disease and chronic

kidney disease in the Western world. Hypertension is also a major risk factor for cardiovascular

disease, which is one of the leading causes of mortality in Westernized countries [69].

According to a meta-analysis, home blood pressure monitoring was reported to be more reliable

than office blood pressure monitoring in predicting cardiovascular events or mortality as well as

helping patients meet target blood pressure levels [70]. Thus incorporation of home

telemonitoring with blood pressure could utilize algorithms that provide decision support to

improve outcomes for patients with other chronic health conditions. In a study conducted at

University Health Network and Mount Sinai Hospital, hypertensive patients with type II diabetes

utilized a mobile phone-based application with wireless self-monitoring of blood pressure. The

intervention facilitated behavior change in the patients without the added use of a healthcare

15

provider or additional visits to the family physician [5]. The use of this mobile phone-based

application was compared to the use of a traditional blood pressure device in a randomized

controlled trial (n=110, mean age of 63 years), and at a 12-month follow-up, there was a

significant decrease in the ambulatory systolic blood pressure in the intervention group [5].

Similarly in another telemonitoring study of chronic hypertensive patients, there were significant

results with the systolic blood pressure reducing by 6.0 mmHg to 10 mmHg while the diastolic

blood pressure reduced by 2.0 mmHg to 4.2 mmHg [57].

There are many factors that determine the effectiveness of telemonitoring. In a study with 588

patients, the patients in the intervention group were required to transmit their blood pressure and

pulse readings every other day, which accumulated to a total of six readings over a 2-week

period [71]. Automated alerts were generated for non-adherence or technical difficulties, which

were then resolved by nurses who would contact the patients to provide support. There were

many technical difficulties that had to be overcome during this study as well as slow response to

resolving the alerts. Studies such as this one showed that poor patient adherence and confidence

would be a limitation to the use of home blood pressure telemonitoring [71]. Another

randomized controlled trial reported an increase in patient engagement in management of their

condition. However, telemonitoring challenged the existing roles and increased the workload for

the clinicians [72]. Factors such as these need to be taken into consideration when designing a

telemonitoring system for blood pressure management, which was to be a component in the

MCC mobile application.

2.3.6 Patients with Multiple Chronic Conditions

Multiple telemonitoring studies have shown the effectiveness of telemonitoring for single

chronic conditions, as highlighted in the previous sections. However, due to the complexity of

patients with multiple chronic conditions, most of the published literature has focused on single

chronic conditions such as diabetes, cardiac diseases, hypertension or pulmonary disease [73].

There was limited amount of literature on effectiveness of telemonitoring for multiple chronic

conditions [23][74], and some of the few existing studies for MCC are discussed below.

16

One study [75] with 205 participants compared usual care versus telemonitoring for comorbid

conditions: myocardial infarction, HF, COPD, DM and renal disease. The telemonitoring system

was composed of peripheral devices that could be attached to a telemonitoring device to measure

weight, blood pressure, blood glucose via glucometer, and oxygen saturation via pulse oximetry

and condition-specific questionnaires. Video monitoring was also available to enable real-time

communication between the patient and their care providers. The telemonitoring group of

patients was asked to perform daily sessions of symptoms and biometric assessment (5-10

minutes) whereas the patients in the usual group only had access to the primary and specialty

office visits. In this study there was no difference found between the telemonitoring group and

the usual care group in terms of reduction in hospital admissions and emergency department

visits. However, in another study with 104 patients diagnosed with HF, COPD and/or DM there

were fewer rehospitalizations in the telemonitoring group (15%) compared to the usual care

group (42%) [76]. This study by Noel et al. [76] utilized a different set of telemonitoring units,

and the telemonitoring system was supported by a nurse triaging the cases. The nurse had access

to a comprehensive electronic patient record (EPR) which enabled patients at home to be more

engaged in taking care of their health due to feedback and collaboration from the healthcare

provider [76]. The participants in the telemonitoring group required a lower number of home

visits from registered nurses, had fewer bed-days-of-care and fewer unscheduled/urgent visits or

need for transportation to the healthcare facilities. Thereby the cost of healthcare decreased by

58% for the telemonitoring group. It is possible that the telemonitoring was successful in this

study because the alerts that were triggered for out-of-range patient data were followed up with

telephone calls. This level of support and accountability encouraged the use of the system and

contributed to the positive outcomes in this study.

A randomized controlled trial (RCT) carried out in 20 health centers in Spain showed that

telemonitoring of in-home patients with HF and/or COPD notably decreased the percentage of

patients who needed hospital care, with a trend showing reduction in cause-specific and overall

hospitalization, as well as a reduction in length of hospital stay [18]. Similarly, a study by the

Veterans Health Administration (VHA) in United States involving the use of

messaging/monitoring devices, video-telemonitors, and videophones for patients with co-

morbidities (33% of 17,025 patients had multiple co-morbidities) to help them live

independently at home showed a 25% reduction in the hospital length of stay, 19% reduction in

17

the number of hospital admissions, and mean satisfaction scores rating of 86% after enrollment

into the telemonitoring program. Studies such as these also denoted that telemonitoring can help

avoid unnecessary admission to long-term institutional care [73].

These large multi-centered studies and much of the discussed literature indicates that

telemonitoring can be effective for MCC. However, these studies did not indicate the use of

mobile phone applications. Mobile phone applications are an inexpensive tool that can be

utilized for reducing the healthcare costs associated with a growing number of people with MCC.

Mobile phone applications have been effectively utilized for telemonitoring of single diseases, as

indicated in previous sections of this paper. Considering that there is a growing spread of mobile

phones worldwide, with mobile phone subscriptions having surpassed the 6 billion mark for the

world’s population of 7 billion [77], it is logical to explore the use of mobile phone applications

as part of telemonitoring solutions for MCC.

There are very limited numbers of smartphone applications available in the market for patient

self-management of MCC. Currently, only one other such application exists called MedDiary

[78]. It is a relatively new application that was launched just a few months prior to the start of

the MCC project described in this paper. The MedDiary platform consists of a mobile device app

for the patients and a web-based portal for the healthcare providers, similar to the architecture of

the Medly system (Figure 3). The MedDiary system helps track food, measurements (blood

sugar, blood pressure, weight), symptoms, activity, sleep, medications and bowel movements,

and it is customizable to the needs of the patient as determined by their physicians. However,

only licensed physicians in the United States and their patients can purchase this app, which

limits the availability of the system to patients and clinicians in other parts of the world.

2.4 Leveraging Existing Technology

Past and current projects from the Centre for Global eHealth Innovation were leveraged to design

the MCC mobile application, particularly those from the Medly system. The Medly system

contained mobile apps for singular chronic conditions to help patients with self-management,

improve communication with clinicians and facilitate greater support for high-risk and complex

patients. The goal for the MCC project was to extend the Medly platform to enable management

18

of multiple chronic conditions through one single mobile application. The MCC application

would not only be usable for single conditions, but also for multiple conditions. In order to

design the MCC platform, the entirety of the Medly system needed to be understood, as shown in

Figure 3.

Figure 3: Architecture of Medly system [79].

The patient-facing component of the Medly system was composed of an Android smartphone

loaded with Medly Apps such as those for HF, COPD and DM. These smartphone applications

enabled patients to collect and store data on a daily basis through short symptoms questionnaires

or via Bluetooth enabled peripheral devices such as a blood pressure cuff, glucometer and weight

scale. The data collected by patients on the smartphone was transmitted and stored in the Medly

Data Server, a data repository at UHN. Clinicians were able to access the patient data through the

Medly Data Server

Clinicians & AdministratorsPatients

Medly Clinical Dashboard

Medly App

BP monitor

Glucose meter

Weight Scale

Android smartphone app

!web interface

automated phone calls

patient alerts

clinic alerts

Medly App• Symptoms monitoring• Medical Device integration via Bluetooth (Weight scale, blood pressure monitor)• Medication monitoring• Physiological trends• Automated self-care messages • Care team information

Application Data Server• Validated clinical algorithms • Clinical and patient alert delivery• Summarize patient reports• Automated email alerts • Automated adherence reminders to patient's home phone

Clinical Dashboard• Patient management• Summarized Symptom and Data monitoring• Medication• Lab Results• Alerts history• Care team • Patient threshold settings• Audit trail and Change history

securedata link

19

Medly Dashboard, a web-based desktop application. In the Medly system, the apps provided

self-care instructions to the patients when appropriate. A nurse monitoring the patients through

Medly Dashboard was providing clinical decision support. However, the apps were able to

generate automated alerts based on readings and symptoms entered or by identification of certain

trends.

Methods 3A user-centered design (UCD) process was utilized to determine the needs and experiences of

MCC patients and clinicians involved in the care of the MCC patients, and to inform the design

and development of a smartphone-based MCC management system. UCD was utilized because it

follows a series of well-defined methods and techniques for analysis, design and evaluation

existing software, hardware and web interfaces to form an iterative development process with the

focus being on the user and making the system usable [80]. Formative semi-structured

interviews were conducted with end-users, which in this case were patients with combinations of

two or more of the following health conditions: HF, CKD, COPD, DM and HTN, and clinicians

with expertise with the aforementioned diseases. Thematic analysis of the interview data

identified needs and barriers for MCC self-management. An assessment of previously developed

telemonitoring systems (such as Medly) and consultations with multiple clinicians informed the

initial designs of a smartphone application for management of MCC. Various designs of the

smartphone application were explored in collaboration with designers, developers and

researchers at the Centre for Global eHealth Innovation. Prototypes were created and tested

through three rounds of iterative usability testing with patients and clinicians. The study was

approved by Research Ethics Boards of University Health Network (#13-7085-BE), North York

General Hospital (#14-0017), and Toronto Academic Health Science Network (#14-0075-E).

20

3.1 Participant Recruitment

3.1.1 Patient Recruitment

Patients for the semi-structured interviews and three rounds of usability testing were recruited

from Family Health Team clinics (a type of primary care model) at Toronto Western Hospital

(TWH), Mount Sinai Hospital (MSH) and North York General Hospital (NYGH) as well as

from the Banting and Best Diabetes Centre at Toronto General Hospital (TGH). A purposive

sampling technique was used to select participants with the following characteristics: 18 years or

older; ability to communicate in English; ability to give informed consent; and diagnosed with

two or more of the specified chronic illnesses. Technology experience and competency with

smartphones was not an inclusion criterion. For the qualitative semi-structured interviews and

first round of usability testing, patients were required to have combinations of two or more of the

following diagnoses: HF, COPD, CKD and DM. For the second and third round of usability

testing, patients were required to have DM and HTN to speed up the patient recruitment because

it was difficult to find patients with combinations of the other chronic conditions. These two

conditions were the most frequently seen combination of diagnoses in the clinics. Thus the focus

of the mobile app design and development shifted to these two chronic conditions in order to

ensure a functional prototype of MCC App would be ready for usability testing within the

allocated time for thesis completion.

Physicians or nurses at the aforementioned clinics identified patients from the clinic’s patient

roster who met the inclusion criteria. Then an administrative assistant, research analyst or a nurse

cross-referenced those patients’ names with the clinic’s patient scheduling system in order to

determine the patients’ next clinic visit. The Study Coordinator (MS) was notified if a patient

had an upcoming clinic appointment, and thus the Study Coordinator was on-site on days when

the patient was to arrive for their appointment. The family physician or nurse meeting the patient

that day would introduce the research study and ask if the patient would be interested in meeting

with the Study Coordinator for additional information. If a patient said yes, then the Study

Coordinator met with the patient to provide additional details and acquire consent if the patient

was amenable. Those providing written consent underwent their first interview or usability

testing session on the same day, immediately before or after their clinic visit depending on the

21

patient’s availability. Meetings with patients were performed in meeting rooms or spare offices

at the three locations.

3.1.2 Clinician Recruitment

Clinicians were recruited for qualitative semi-structured interviews and for two rounds of

usability testing. Medical specialists and a pharmacist from specialized clinics as well as family

physicians, nurses and a pharmacist from primary care clinics were recruited. The medical

specialists and a pharmacist were from Asthma and Airway Centre at TWH, the Heart Function

Clinic or Renal Clinic at TGH. The family physicians, nurses and a pharmacist were from the

Family Health Teams at TWH and MSH. Clinicians were sent an email and/or information letter

to ask them if they would be available to participate in an interview or usability testing of the

mobile monitoring system. Consent was obtained during the interview and usability sessions.

These sessions were conducted at the provider’s clinic or Centre for Global eHealth Innovation.

3.2 Data Collection and Analysis

3.2.1 Phase I: Requirements Gathering through Formative Interviews

One-on-one semi-structured interviews were conducted with patients and clinicians. A total of 15

patients agreed to be interviewed over an 8-month period (May – December 2014); and a total of

10 clinicians were recruited for semi-structured interviews over a 7-month period (March –

September 2014). Family members of the patients were present during some of the interviews.

The patients were asked to complete a pre-study questionnaire prior to the interview in order to

provide demographical information and information about their ease with using smartphones and

cellphones (Appendix B). During the interview, participants were asked open-ended questions to

get a sense of their needs, concerns, goals and expectations concerning management of multiple

health conditions and using the information to guide delivery of an intervention as part of self-

management support [81]. The patient interview guide was adapted from one developed by the

Bridgepoint Collaboratory for Research and Innovation, and has been used previously for

research with older adults with MCC in primary care settings [23][82][83]. The interview guide

22

included questions on patients’ goals and frustrations while managing multiple health conditions

including their medications, treatments, symptoms, and care provided by different healthcare

providers. For the current study, questions on remote patient monitoring and use of technology

were added in order to understand patients’ comfort with using mobile phones and computers

(Appendix E). The clinician interview guide was adapted from those used previously at the

Centre for Global eHealth Innovation to include questions about multi-morbidity and chronic

conditions HF, CKD, COPD, DM, and HTN (Appendix D). Cognitive interviewing with a

primary care physician and two staff members from the Centre for Global eHealth Innovation

were performed to ensure the questions in the interview guides would make sense to the patients

and clinicians.

Sample patient questions that were asked were:

• Do you have any difficulties managing your health conditions? [Cue: If yes, can you

please describe what you find difficult?]

• What are some day-to-day activities you do to help you manage your conditions?

• Based on what we have told you about the mobile app, do you think it will be helpful for

you?

Sample clinician questions that were asked were:

• What are some current challenges that you as a clinician experience with providing care

for patients managing multiple chronic conditions?

• What do you think can help your patients with multiple chronic conditions improve their

own self-management?

• Do you think a mobile app for remote monitoring can be helpful for managing multiple

chronic illnesses?

Notes and audio recordings of the session were taken for record keeping purposes after written

consent from the participant was obtained. The Study Coordinator (MS) transcribed the 15

patient and 10 clinician interviews. All recordings and notes were kept confidential and shared

amongst the study team only. All information obtained during the study was held in strict

confidence, and participant information was only identified through a coded identification

number.

23

Qualitative analysis was conducted by the Study Coordinator (MS) concurrently with participant

recruitment, which was halted when saturation was achieved i.e. no new concepts were arising

from new interviews. A mix of inductive and deductive methods was used in the analysis of the

recorded notes. Deductive content analysis uses existing theory or pre-determined categories to

guide the content analysis [84]. In inductive analysis, researchers avoid using preconceived

categories, instead allowing the categories and names to flow from the data [84]. For this study,

notes were reviewed repeatedly and analyzed to derive major themes that were relevant to the

research questions. The health belief model (HBM) was used to frame the analysis (hence

deductive analysis). However, the analysis was not constrained to any particular construct of the

HBM and the data were categorized freely to identify barriers and motivational factors (hence

also inductive analysis).

The constructs of HBM were specifically utilized to guide the thematic analysis of the interviews

with patients to identify barriers and facilitators for self-management of chronic conditions.

Perceived susceptibility was utilized to learn about the individual’s assessment of his or her

chances of getting a condition or disease. Perceived severity was utilized to understand how

feelings about the serious of the disease including evaluations of the medical consequences (e.g.

pain, disability) and social consequences (e.g. effect on work, family, life, social relations)

affected patient’s perception towards self-management of their health conditions. Patients’

adherence to self-management actions was analyzed based on their perception of perceived

benefits (e.g. effectiveness of medications) and perceived barriers (e.g. side effects of

medications). Cues to action was utilized to understand what encouraged self-management

actions (e.g. printed reminders). Self-efficacy was used to understand patient’s convictions that

he or she could make successful changes and ability to take action to change behavior (e.g.

making an effort to eating healthy and exercising regularly). Thematic analysis of clinician

interviews was performed separately from the patient interviews in order to identify barriers and

facilitators faced by clinicians in providing proper care for MCC patients. A Second Reviewer

conducted the same analysis. Both the Study Coordinator (MS) and Second Reviewer were

Master’s students with training in health, engineering and/or human factors. Each transcript was

reviewed and coded independently by the two researchers, who later met to discuss and achieve

consensus on final themes. Themes and sub-themes that emerged were used to inform the design

of the self-management mobile application.

24

3.2.2 Phase II: Leveraging Existing Applications to Design Prototypes

In order to design an MCC self-management smartphone application based on the needs of users

identified through semi-structured interviews, the common and conflicting features of the

existing self-management mobile apps were analyzed. Algorithms and content from previously

developed telemonitoring apps were leveraged which had been vetted by specialists at UHN,

North York General Hospital and Sick Kids Hospital and were being evaluated at various stages

of clinical trials. Algorithms for COPD exacerbation pathway, reminder notifications, history,

subroutines for HF application’s generation of alerts, blood pressure algorithm for CKD

application, generation of trend reviews and alerts for DM application were studied and

comparisons were made in order to determine how to resolve the issue of creating one mobile

application that enabled user to manage multiple conditions. The content between the apps were

compared such as the symptoms questions for CKD, HF and COPD applications. Guidelines for

management of singular chronic conditions published by Canadian Hypertension Education

Program, Canadian Thoracic Society, Canadian Cardiovascular Society, etc. were utilized in

order to determine objective requirements for MCC application, such as frequency of blood

pressure readings required for HTN patients versus HF patients. Furthermore, consultations with

specialists as well as primary care clinicians occurred at various stages of the project while

developing the content for the MCC smartphone application. Various designs and content of

MCC were explored in collaboration with designers, developers and researchers at the Centre for

Global eHealth Innovation. As part of the user-centered approach, prototypes were designed and

refined based on the information that was gathered through qualitative interviews with patients

and clinicians as well continued information gathered through guidelines and consultations with

professionals.

3.2.3 Phase III: Iterative Usability Testing

Usability testing is an observational research technique where representative end users are

recruited to participate in scenarios in a simulated environment in order to assess the

appropriateness and ease of use of a system [80]. All patient and clinician participants for the

25

usability testing were asked to sign a written consent form prior to the start of the study. The

central premise of involving end users in the development of MCC self-management application

was that optimal solutions result from understanding the needs of the people who will use them.

Upon meeting the participants, the purpose and objectives of the evaluation was explained to

each participant. Participants were informed that they would be observed, audio taped and

screens of the phone app would be videotaped to record where they are tapping. Participants

were provided with a brief overview of the application. Patient participants were asked to

complete a pre-study questionnaire, the same one that was used for semi-structured interviews to

provide information on demographics and ease in using smartphones or cellphones (Appendix

B). However patients who had already participated in the semi-structured interviews were not

asked to complete the pre-study questionnaire again.

The first round of usability testing was conducted with 6 patients (November – December

2014) and 4 clinicians (November 2014 – January 2015). The patient participants were the same

as those the study coordinator met for semi-structured interviews because the usability testing

followed the interview session. The Study Coordinator (MS) had created designs for each screen

of the mobile application using PowerPoint based on the features and design principles identified

through qualitative interviews with patients and clinicians in Phase I as well as taking into

consideration the features of the smartphone applications at the Centre for Global eHealth

Innovation. Designs were updated iteratively based on new information gathered during the

usability testing sessions with the users. The Study Coordinator transferred the designs onto

Flinto (an online tool for prototyping of iOS and Android applications for user interface and

experience testing) to create an interactive prototype on Samsung Galaxy S4 that allowed users

to navigate through a realistic looking mobile application. The first round of usability testing

was conducted at the FHTs in TWH, MSH and TWH.

The second round of usability testing was conducted with 5 patients (June – August 2015) and

7 clinicians (May – June 2015). None of the 5 patient participants in this round had been

previously recruited for this study, however three of the clinicians in this round had participated

in the semi-structured interviews and/or first round usability testing previously. The designs of

the smartphone application had gone through multiple iterations with feedback from designers,

developers and other members of the PHIT team at the Centre for Global eHealth Innovation

26

since the first usability testing. The Study Coordinator created multiple design iterations on

PowerPoint to explore different ways of navigating through the smartphone application and

resolving issues related to the presentation of information on different screens. Multiple product

review and discussion meetings were conducted with members of the PHIT team. Once one of

the designs was decided upon, then the Study Coordinator transferred over the PowerPoint

screen designs to a UI/UX designer from the Healthcare Human Factors team at the Centre for

Global eHealth. Updated designs with improved graphics were created using Sketch, a software

for graphic designing similar to Adobe Photoshop. The Study Coordinator and the designer

collaboratively updated designs based on continued meetings with team members from the

Centre for Global eHealth Innovation. Due to continuous improvements in design details, an

interactive prototype was not created. Instead paper prototypes were utilized for the second

round of usability testing. In the first round of usability testing, the designs were created for a

sample user who had to measure four parameters: weight, blood pressure, blood glucose and

symptoms due to having HF, COPD, DM and CKD. However patient recruitment had been slow

for these conditions, so the designs for the second round of usability testing were focused on

patients with DM and HTN because this was a commonly seen combination seen in the primary

care clinics and hence sped up the patient recruitment process. The second round of usability

testing was both conducted at the FHTs in TWH and MSH.

The third round of usability testing was conducted with 5 patients (August – September 2015)

at the Diabetes Clinic Banting and Best Centre. None of the participants in this round had been

previously recruited for this study. The criteria for the patient recruitment was: HTN and DM. A

functional MCC application had been developed for this final round of testing, with functioning

Bluetooth connectivity, allowing users to explore the app to a far greater extent than the previous

usability tests. Patients were asked to measure blood pressure and blood glucose readings. A

commercially available digital blood pressure monitor and glucometer were utilized for taking

measurements, which transferred from these external devices to the Samsung Galaxy Core

smartphone, which had the pre-installed MCC application. A blood pressure simulator with

preset readings was utilized for various scenarios. None of the users were asked to prick

themselves for the blood glucose measurements. Instead, sample glucose solutions were utilized

for the different scenarios.

27

The usability testing investigated the users’ ability to enter and access information in terms of

ease of use and efficiency. The participant was asked to interact with the application. A sample

of the interactions that the user may be asked to perform within the application include:

• accessing the application

• navigating through the application

• searching for and reviewing information

• adding new information

• editing of omitting information

The results of this research were expected to highlight key issues associated with the application

and inform decisions for future design iterations. The study lasted maximum 1 hour and the

testing environment was set up with a desk and chair for the participant to sit.

After completing the usability testing session, the Study Coordinator (MS) debriefed the

participants. This informal interview was exploratory in nature to further understand any issues

arising during the experiment. Sample questions that could be asked included:

1. Can you please describe your experience using the application?

2. Were there aspects of the application that you found frustrating? Why?

3. Were there aspects of the application that you found easy to use? Why?

4. What would you change about the application to fit your needs?

The participants in third round of usability round were additionally asked to complete a post-

study questionnaire (Appendix C) pertaining to their perceptions of the usability of the

application, specific issues or areas for improvement.

Notes, audio and video recordings of the session were taken for record keeping purposes after

written consent from the participant was obtained. The Study Coordinator (MS) used the video

recordings for data analysis, to visualize preferences and interpretation of the app design. All

recordings were kept confidential and shared amongst the study team only.

28

Results 4

4.1 Phase I: Requirements Gathering using Formative Interviews

Semi-structured interviews were conducted with 15 patients and 10 clinicians. Around half the

patients (8/15, 53%) were recruited from the patient roster of one the clinicians who were

interviewed. In contrast, 4 of the 10 providers (40%) had patients who were included in the

study.

4.1.1 Participant Characteristics

Patient participants for semi-structured interviews were recruited over a 6-month period (July –

December 2014). The socio-demographic characteristics of the patients are presented in Table 1.

The age range of patients was 51-83 years, with a higher proportion of them (60%) being over

the age of 65. A higher proportion of men (67%) agreed to be interviewed for this study than

women (33%). The interview sessions lasted 45 minutes to 1.5hours, depending on the time it

took to explain the study, clarify any questions or concerns, complete the consent process, and

the amount of time the patient was available before they had to go for their subsequent

appointments, work, car parking, or wheel trans pick up. Of the five chronic conditions that were

included in this study i.e. HF, COPD, CKD, HTN and DM, a total of 5 patients (33%) had three

of the required conditions, while the remaining 10 patients (66%) had combinations of only two

of the required conditions (Table 1). Nevertheless, there was a high prevalence (93%) of other

commonly reported conditions such as hyperlipidemia and arthritis, as well as asthma,

atherosclerosis, back pain, chronic pain, Crohn’s disease, deep vein thrombosis, depression,

herniated disc, obesity and psoriasis. Most patients mentioned regular visits with their health care

providers, including primary care physicians or nurse practitioners; medical specialists;

dieticians, diabetes educators; and pharmacists.

In terms of usage of technology (Table 2), 80% (12/15) of the patients interviewed did not own a

smartphone. However, all three of the patients who owned smartphones were comfortable or

very comfortable using it and were active in using their smartphones for web browsing, emails,

scheduling, information seeking and other activities such as playing games. They were also more

tech-savvy compared to the most of the other patient participants, because these patients also

owned a desktop or laptop, which they used constantly or frequently. In comparison, most of the

29

other patient participants who did have a computer at home, they only used it sometimes, rarely

or never. The patients who never used a computer despite having one available at home were

those living with other family members such as grandchildren or children, so although a

computer was available at home, they did not make use of it.

Table 1: Patient demographics for semi-structured interviews.

Characteristics

N (n = 15)

Age 18 – 39 years old - 40 – 64 years old 6 >65 years old 9

Gender Female 5 Male 10

Highest Education Received

Elementary - High School 5 College/Undergraduate 7 Post-Graduate 3

Chronic Conditions for Study Eligibility

HTN + DM (Oral Meds) 3 HTN + DM (Insulin) 4 HTN + COPD 1 DM (Oral Meds) + COPD 1 HF + COPD 1 HF + COPD + DM (Insulin) 1 HF + COPD + DM (Oral Meds) 1 HF + HTN + DM (Insulin) 2 CKD + HTN + DM (Oral Meds) 1

Although 12 out of 15 patients did not own a smartphone, more than half of them did own a

cellphone. All 8 cellphone owners were somewhat comfortable, comfortable or very comfortable

with using their cellphones, but they were not avid cellphone users. The main purpose of the

basic cellphone owners was to be able to make urgent or emergency calls and hence the

frequency of their cellphone usage was much lower, as shown in Table 2. Seeing that the target

population is elderly and not heavy users of technology, one of the design considerations during

the app development was to keep the app simple to use and easy to understand.

The 10 clinicians for semi-structured interviews were recruited over a 9-month period (March –

September 2014). Two of the clinicians were specialists, one in HF and the other in COPD. One

clinician was a pharmacist from a CKD clinic. Seven of the clinicians were primary care

physicians or nurses from the family health teams.

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Table 2: Technology-related characteristics of patients in the semi-structured interviews.

Total (n=15)

N

Smartphone Users (n=3)

How comfortable are you using a smartphone?

Very comfortable 2 Comfortable 1 Somewhat comfortable - Not comfortable -

What type of smartphone do you use? Blackberry 1 iPhone 2 Android -

Please estimate how often you use your smartphone.

Frequently (few times a day) 3 Sometimes (few times a week) - Rarely (few times a month) - Never -

Please indicate the activities you use your Smartphone for.

Voice calls 3 Text messaging 2 Email 2 Information seeking 3 Scheduling 2 Information storage (e.g. contacts) 3 Other -

Cell Phone Users (n=8)

How comfortable are you using a cellphone?

Very comfortable 1 Comfortable 2 Somewhat comfortable 5 Not comfortable -

Please estimate how often you use your cellphone.

Frequently (few times a day) - Sometimes (few times a week) 5 Rarely (few times a month) 3 Never -

What features do you use on your cell phone?

Voice calls 8 Text messaging 6 Web browsing - Other -

Desktop or Laptop Owners (n=5)

Please estimate how often you use your desktop or laptop.

Frequently (few times a day) 3 Sometimes (few times a week) 2 Rarely (few times a month) 2 Never 2

Glasses or Contact Lenses (n=12)

Do you use your glasses/contact lenses for distance or reading?

Distance 1 Reading 5 Both Reading and Distance 6

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4.1.2 Themes Generated from Interviews with Patients and Clinicians

Seven themes were identified using the constructs of the HBM model in search for barriers and

facilitators to self-management of multiple chronic conditions. The thematic analysis was not

limited to any particular constructs, but the emerging subthemes predominantly identified with

barriers to adoption and cues to actions, which were identified as barriers and facilitators for a

MCC self-management system. Initially ten themes had emerged from the patient interviews and

ten themes from clinician interviews. However, it was realized that many of the patient and

clinician themes were interrelated. For example, based on the clinician interviews, it was

determined that the level of monitoring required for patients depends on the severity of their

health conditions, and similarly the patient interviews demonstrated that there is much variance

in the self-management regimens among patients due to the differences in the severity of their

health status. Thus common or related themes and sub-themes between clinicians and patients

were merged, resulting in seven themes and corresponding subthemes shown in Table 3.

Features that could be incorporated into the MCC self-management system were proposed and

whether those features were integrated or not are also clarified in Table 3.

Table 3: Summary of themes, subthemes and corresponding features.

Themes Subthemes Origins of Subtheme

Proposed Features Scope

A: Tailor the intervention to the unique needs of the patients.

A1 Collecting for multiple parameters may become burdensome.

Patient and Clinician Interviews

Patient should monitor parameters that are deemed necessary for management of their combination of health conditions.

Integrated into MCC App v1.0

Data collection should be automated as much as possible to minimize the burden of collecting data.

Bluetooth enabled devices are integrated with MCC App v1.0. Transfer of data from external databases is possible through Medly Dashboard.

A2 Level of self-care activities depends on severity of condition.


Frequency of monitoring required should be flexible.

Issue explored. Limited development.

B: Teach self-management skills to improve health outcomes.

B1 Patients want to minimize deterioration in health.

Patient Interviews

Provide a preventive tool to send an alert or notification to the patient at the earliest sign of

Integrated into MCC App. Alerts or notifications are displayed on the app

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deterioration in health. based on HTN and DM algorithms.

B2 Patients have difficulties establishing or maintaining healthy lifestyle habits: • Diet • Exercise • Weight • Smoking • Alcohol


Help patients keep track of what they consume, their level of physical activity and weight measurements.

Future

Guide patients through proper exercises for people with physical limitations

Future

Inform patients about proper foods based on established guidelines

Future

Provide evidence-based smoking cessation methods

Future

Provide evidence-based guidance for reducing alcohol consumption

Future

Provide patients with methods of pain management.

Future

B3 Educate patients about their health conditions.


Reinforce the educational component through daily tips.

Future

Instructions and content of the app must be validated by clinicians

Integrated into Medly MCC v1.0.

B4 Guide patients to properly respond to changes in signs and symptoms.

Clinician Interviews

Utilize the collected data to provide actionable feedback.

Explored use of daily tips.

C: Streamline the self-management activities.

C1 Patient adherence may improve with organized routines.

Patient Interviews

System should require patients to carry out self-management activities at consistent times/schedule to help establish a routine.

Future

System should make use of reminders to help patients remember to perform self-management actions.

Future

C2 Patients lack proper resources to streamline record keeping.

Patient Interviews

System should enable patients to consolidate, store and manage their personal health information in a better way.

Partially integrated into MCC App v1.0.

C3 Involve patients in maintaining an updated medications list.


System should help patients and clinicians stay updated on the medications list, by having timestamp of last update and by whom.

Designed but not developed for MCC App v1.0.

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D: Provide resources to reduce conflicting advice.

D1 Patients may receive conflicting advice from different clinicians.


Monitor specific parameters and enable clinicians to view and adjust target ranges based on how patients respond to treatments.

Possible through Medly Dashboard in future.

D2 Lack of evidence-based guidelines for multiple chronic conditions.


Large-scale frameworks by healthcare systems are needed to develop evidence-based guidelines for management of various combinations of conditions.

Future

E: Make appropriate use of the collected data.

E1 Clinicians have limited time to review all data.


System should provide interpretation of the data or summaries of the data where possible to save clinician time reviewing patient history.

Partially integrated into MCC App v1.0.

E2 Graphical trends demonstrate changes overtime.


System should provide a graphical view of the data points that patients collect so that they can see the progress or decline overtime.


F: Use the alerting system reasonably.

F1 Alerts enable clinicians and patients to be proactive.


System should have a mechanism to alert the clinicians, which could shorten the time to address the problem.


F2 Need to determine who needs to be monitoring alerts.


System should involve a clinician who can direct alerts to the most responsible person for that issue, with notifications to the other clinicians involved in the care.

Issue explored with team and clinicians.

F3 Alerting system should not disrupt clinicians’ current workflow.

Hierarchy of alerts should be created in which the more critical alerts are sent to the clinicians.

Created hierarchy of alerts. Level 4 sent to clinician.

G: Establish efficient communication

G1 Patients have difficulties making visits to multiple doctors.


System should enable patients to share their health information with their doctors through the use of web-interfaces.


G2 Communication between multiple healthcare providers is inefficient.


System should enable multiple healthcare providers to have quick and secure availability to a central repository where data captured by


34

patients and related to the patients’ health conditions are held. Inter-clinician communication system should be developed.

Future

Mobile app should contain a list of care providers and their contact information

Designed but not developed into MCC App v1.0

The majority of the interviewed patients were interested in trying out the proposed self-

management mobile application in future studies, provided that it would provide them with

necessary guidance. The following section contains detailed explanations of themes and

subthemes listed in Table 3.

Theme A: Tailor the intervention to the unique needs of the patients.

Patients with multiple chronic conditions experience barriers to self-care due to the simultaneous

and competing demands of their conditions. Additionally, the self-care support needed among

the patients varied with the number of chronic conditions and severity of the conditions.

Therefore, an intervention aiming to help patients with self-management should be tailored to the

unique needs of the patient based on the level of care they need to best manage their health.

Subtheme A1: Collecting data for multiple parameters may become burdensome.

All patients expressed that they wanted to maintain or improve their health as much as possible,

and most were willing to take actions that would minimize the chances of their health conditions

getting worse. However, patients expressed that they would prefer to “have as little intervention

as possible” [P1]. Clinicians were also supportive of having an intervention that would help

patients collect and share clinical data in between their clinic visits to improve the quality of

decisions that were made regarding their health: “Really for us, it gives us the potential of

finding out more about the patients when they are not in the office; things like the vital signs,

like blood pressure and weight can be quite useful. That part is actually what I see as being the

most useful” [C4]. However, clinicians identified that different parameters need to be monitored

for different chronic conditions. For example, one clinician identified that for self-management

of HF, the main factors were changes in weight, blood pressure and symptoms. For CKD, the

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main factors were blood pressure, blood work, creatinine and urine testing. For COPD, lung

function tests and monitoring of symptoms was deemed important. For DM, blood glucose

levels, health behaviors, and maintaining a diabetic diet were said to be important. There was

some variance in factors deemed to be important for each of the chronic health conditions, but it

was clear that in order to ensure patients were not overburdened by self-monitoring, we must

“pick a couple of major markers, not a lot” [C7] depending on what data the patients can actually

collect by themselves at home and what data can be collected from external clinical databases.

Proposed Features – Subtheme A1

Taking into consideration that patients have various combinations of chronic health conditions

and different parameters to monitor for different conditions, the mobile application should be

customized so that each patient views parameters that are specific to their set of needs.

Having additional parameters that are not applicable to a patient will cause confusion in self-

management practices. It could further cause patients to be overwhelmed if the application

requires them to make unnecessary measurements unrelated to their health conditions, leading to

non-adherence or improper self-management practices. Furthermore, data collection should be

automated as much as possible to minimize the burden of collecting information. This can

be done through the use of Bluetooth-enabled devices and transfer of clinical data from external

databases ex. lab results and medication lists.

Subtheme A2: Level of self-care activities depends on severity of conditions.

Clinicians clarified that there was a difference in the severity of health condition among patients

observed in the primary care clinics versus those in tertiary clinics, and levels of monitoring

required depended on the severity of the health conditions. Patients in tertiary specialized clinics

were those whose condition had deteriorated to a severe state. For example, a clinician from the

CKD clinic stated: “Patients who come to our clinic are sicker so they need closer monitoring.

Stage 1 patients, they don’t come to our clinic. They go to see general nephrologist, they could

use maybe a lighter version because these patients in the earlier stages don’t need the close

monitoring. However they could benefit from the education about things that they can do on their

own. They won’t be too dependent on this app” [C1].

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In contrast, primary care clinics tend to see patients with milder forms of chronic conditions:

“Primary is responsible for the totality of their health. In primary care, they have a milder form

of all the diseases. At primary care we will have more people in the mild levels and fewer in the

severe levels. Prevent the mild from getting more severe, because there wouldn’t be a large

application at the primary care level if you focus on the advanced level of any of these

conditions” [C2].

Interviews with the patients also exemplified that their needs for monitoring and type of self-care

activities differed based on the severity of their illness. There were two different groups among

patients on what type of self-management strategies they followed. Patients who were younger,

in their 50s or early 60s, and had been living with their chronic health conditions for a shorter

period of time, were more inclined towards not adhering to the monitoring and medications that

were prescribed to them by their doctors. One 61-year-old patient with hypertension, diabetes

(non-insulin) and high cholesterol stated, “I’ve never taken mediations, maybe aspirin once in

couple years. The medications typically do not sit very well with me. I don’t feel well so I avoid

them. My guess is that most patients take their medications and that’s the end of it. I’m not very

keen on it” and “No I don't take my blood glucose measurements. I know [the doctors] think I

should, but I don’t” [P1]. The younger patients instead preferred making lifestyle changes, such

as getting more exercise (ex. walking back and forth to work) and making substantial changes to

their diet in order to improve their health, with one 54-year-old patient stating, “diet and exercise

are my mantra” [P10].

Conversely, patients who were older and had their chronic conditions for a longer period of time

were more open to performing the daily medication regimen and measurements needed to keep

their health conditions under control. To continue with the self-management practices

recommended by their health care providers, patients had to experience some effect or believe

the self-management practices were effective. One 72-year-old patient measured her blood

glucose levels daily as recommended by the doctor and kept a record of her measurements in the

logbook given to her by the diabetes team. Another 70-year-old patient said he used to measure

his blood pressure once a week, but now had started to measure it twice a day because it had

been high for the past while. Similarly, another 71-year-old male patient with HF, DM and other

chronic conditions followed his doctor’s recommendations by measuring his weight shortly after

waking up i.e. after the washroom, before having breakfast. Then the patient would measure his

37

blood pressure in late morning, and would also take his blood glucose readings in the evening.

So despite having same chronic conditions, there was a variance in patients’ self-management

regimens based on how long they had been living with their chronic conditions.

Proposed Features – Subtheme A2

The needs of patients in primary care clinics versus specialized clinics are different. Designing

an app for a specialized clinic enables the design to be more focused. However, primary care

clinics see a wide range of patients and designing an app that caters to the needs of many

requires careful consideration. To make the mobile application usable for a more general

population of patients, such as those in the primary care clinics, the frequency and type of

monitoring should be more flexible. Collaboration with clinicians would clarify what

frequency of measurements is required.

Theme B: Teach self-management skills to improve health outcomes.

Patient want to minimize deterioration of their health and most are open to guidance that will

assist them in improving their self-management skills. They seek information and help from their

healthcare providers, family and friends, as well as from the Internet and books. However, many

of the MCC patients are older and experience difficulties in maintaining healthy lifestyles due to

factors such as pain, physical limitations, financial constraints and lack of motivation. Therefore,

interventions that not only provide knowledge about their conditions, but also train them to

respond to their health situations as best as possible will be beneficial for them to become more

self-aware and better able to manage their day-to-day care.

Subtheme B1: Patients want to minimize deterioration in health. All patients in the study had two or more chronic health conditions, and one of the overarching

concerns was the ongoing anticipation of having to deal with worsening or developing additional

health conditions in the future. There were various motivations for patients to engage in self-

management behaviors to minimize worsening of their health conditions. Sometimes it was

concerns about being a burden to the family members if their health conditions worsened: “My

goal is to not be a burden to my kid. My contribution to the family is to keep myself healthy and

don’t give them extra troubles of a sick mother” [P4]. Others simply wanted to “minimize the

38

number of ailments that arise as you get old” [P1]. Patients also spoke about their fears of pain

and possible serious complications, which motivated them to take precautionary actions. One

patient for example made the effort to measure her blood pressure and take medications when

she was in discomfort: “When I have high blood pressure, I feel neck pain and in shoulders.

When that happens, I think it’s my blood pressure. I go to the pharmacy, and I measure my blood

pressure. I [also] take my medications. I don’t go to emergency” [P3]. The sense of

susceptibility due to uncertainty and anticipation of problems was a common concern among the

patients, acting as a motivator for patients to watch for signs of deterioration of health.

Proposed Features – Subtheme B1

Patients anticipate the occurrence of problems related to their health conditions and fear the

possibility of losing the power to act or take necessary actions to minimize the worsening of their

conditions. Therefore, the mobile application should act as a preventive tool and send an alert

or warning message to the patient at the earliest sign of deterioration.

Subtheme B2: Difficulties establishing or maintaining healthy lifestyle habits.

All patients realized there were benefits to making lifestyle changes whether it was weight, diet

and exercise management, or whether it was quitting smoking and alcohol. Many patients

identified maintaining proper diet to be one the most problematic self-management behaviors

due to factors such as having to limit foods high in salt or carbohydrates, eating at the right

times, breaking old established eating habits, boredom from maintaining healthy diet, not having

enough information on proper diet or financial constraints. Carelessness emerged in relation to

inconsistencies in maintaining diet behaviors, especially with regard to handling food craving

and holiday eating. Diet management was not isolated to any one particular health

condition. Patients were trying to maintain healthy diets for multiple common health conditions

such as diabetes, cardiovascular disease, hypertension, dyslipidemia and obesity.

Physical activity and weight control were also seen as beneficial across multiple conditions,

with some patients making an effort to integrate exercise into their schedules: “I lost 25lbs. I eat

healthy, exercise - walk 30min to 40min everyday. I started this 1 year ago. I consciously made

the effort to change” [P10]. Few patients were interested in monitoring their activity levels, such

as one 61-year-old patient who used a Fitbit to monitor his activity levels. However, others were

39

less interested such as a 59-year-old patient who stated that he would not find tracking his

walking and physical activity useful, because “I know I walk the same route. I know how fast I

walk” [P2].

Adjusting to the constant presence of health problems involves a change in thinking and

behavior. While many patients wanted to make lifestyle changes, some were more reluctant to do

so, such as a patient who continued to smoke and consume large quantities of alcohol: “I smoke

one pack a day. It’s absolutely affecting my COPD. I don’t believe I want to stop smoking.

That’s the problem. Probably how I got it. No one has really offered me any advice” [P9] and “I

am an alcoholic. I certainly don’t have the problem I used to. I certainly can’t drink the way I

used to. I’m getting old. [The family doctor] told me to cut down, but that isn’t going to happen”

[P9].

Many patients were also limited in their abilities to establish healthy lifestyle habits due to pain

and physical limitations. Their physical activity was limited or prevented by pain in joints from

arthritis, pain in feet from neuropathy, or low endurance and fatigue. One 81-year-old female

patient stated, “I can’t exercise. I also have osteoarthritis. They did advice me to walk, but I

can’t. I get half a block, and it gets so painful.” Pain and physical limitations apply across

multiple health conditions, and patients could be suffering from pain due to a combination of

health conditions. For example, one patient’s husband described that his wife was physically

limited by diabetic neuropathy as well as arthritis: “She has to exercise but she thinks that the

emphasis is on proper meat and vegetables and fruit. We check her blood sugars 3 to 4 times a

day, but her feet are affected, due to neuropathy. She has to use a walker outside and cane inside,

and left foot has a brace. She has arthritis in the ankle and throughout the foot.”


Patients have expressed frustration in having to maintain or establish healthy lifestyle habits, but

at the same time many have also expressed their commitment to trying to do so because it is

important for maintaining their health. There is potential in having a mobile application app that

helps patients manage their daily lifestyle habits such as diet, weight, exercise by helping them

keep track of their food and drink intake, their activities and weight measurements. The

mobile application could be used for providing information on proper exercises for people with

physical limitations as well as proper foods based on established guidelines. Further

40

evidence-based smoking cessation methods and guidance for reducing alcohol consumption

can be of further assistance to patients. Additionally, pain is one the biggest factors limiting

patients’ ability to effectively self-manage their health, as confirmed by patients in this study and

established in multiple other studies [21]. Therefore, pain management can also be feature to

incorporate for a mobile application aiming to help MCC patients.

Subtheme B3: Educate patients about their health conditions.

Self-management starts with patient education [85]. One primary care physician explained

“education goes across the board for everybody” when he was asked what are the top two factors

required for self-management of each of the conditions in this project. Other clinicians echoed

this as well. Most patients found their healthcare team to be a great resource. One patient stated

that his family doctor was “Great. He provides great resources, pamphlets to read” [P10].

Patients also sought information about self-management from talking to their health care

providers, family and friends, as well as searching for information in the library or Internet.

However, as one clinician pointed out “many patients will Google information which is not

always correct or accurate; so filtering info would be helpful.” Health care providers are largely

the most reliable source of information. One patient for example stated: “Long time ago I went to

the library to read about diabetes. If I’ve got a question now, I just call into this clinic. I didn’t

understand what Type I and Type II and I didn’t need insulin at that time, so I didn’t know if I

should and shouldn’t. And what symptomology I should experience” [P2].


For many patients and their families, the journey into self-management starts with education,

learning the technical skills related to their specific conditions. The mobile application can

reinforce the educational component by providing daily tips that encourage them to practice

healthy lifestyle and self-management behaviors, and help them to understand the benefit or

potential outcome of the self-management behaviors. However, considering that patients rely on

the advice of their doctors to a great extent, the app must should not explicitly guide or provide

the patients with clinical decision support, but must contain instructions that have been

validated by clinicians or are general enough that the instructions do not cause liability issues.

41

Subtheme B4: Guide patients to respond to changes in signs and symptoms.

Multiple clinicians identified changes in symptoms and changes in parameters as an item that

patients should be made aware of and taught to take appropriate actions: “It’s an understanding

of the changes of their symptoms, alert them to notify us. Having an action plan and knowing

how to act is important. Most people would be a milder situation, where they can contact us, talk

to the nurse in the urgent basis, and then you can decide where to go – appointment, ER, etc.”

[C9]. Multiple clinicians saw the potential in using a smartphone application to teach patients

about changes in their conditions. Based on changes in the recorded signs and symptoms, the

mobile application could simply tell the patient to contact their healthcare provider as opposed to

providing detailed medical instructions, as stated by a HF specialist, “The key thing is that they

properly alert us when they are experiencing problems… Remember that people with HF can get

other heart problems. Any change in their condition, they should call. Mild HF patients are going

to be infrequent. But those with overt HF episodes need regular monitoring.” The same was

stated by a CKD specialist, “We want to address those symptoms and see how it’ll do with CKD.

Allow us the opportunity to know what it is going one so we can intervene.”


The mobile application should use the collected data to provide patients with guidance on

what actions to take next. Help them recognize changes. The app should contain algorithms

that utilize the data collected by patients, such as the measurements they take, blood pressure,

heart rate, weight and symptoms the patients record, and provide actionable feedback. The

algorithms should look for changes and patterns over time in order to trigger alerts or

notifications to the patients.

Theme C: Streamline the Self-Management Activities

Patients with MCC have multiple healthcare providers, several different medications and

different actions to take on a frequent basis to monitor and maintain their health conditions.

Streamlining the actions and helping patients organize their daily medications, treatment plans,

monitoring schedules etc. could improve patient adherence to their treatments.

42

Subtheme C1: Patient adherence may improve with organized routines.

Patients who had created routines and had managed to figure out self-management strategies that

fit into their life appeared to be more adherent to the self-care practices. Routines helped patients

both remember and carry out self-management behaviors efficiently by making day-to-day

decision-making easier. When asked what might help him in managing his health conditions, one

patient answered, “maintaining a schedule” [P11]. Patients with self-management routines did

not need to reflect on their decisions each time they performed a self-management activity: “And

I’m trying to organize and it’s become a routine. That’s the key word. But perhaps before the

routine, you have to figure out how to and everything” [P4].

Patients described some of the routines that had become such a part of their daily lives that they

no longer consciously thought about them. For example, to encourage themselves to get some

exercise, patients would perform the same physical activity every day: “I walk back and forth to

work. That is an hour and half. No workout during the weekend” [P1]. To ensure they ate

properly for diabetes control, patients would have a scheduled diet: “Whole wheat bagel with

butter, tea no sugar. Then meds. Break time another bagel. Banana. Lunch time, and then dinner”

[P7]. Many patients developed routines for organizing their medications and learned to plan

ahead to ensure they took their required medications: “I use pillboxes. I concentrate and put 7

days of pills. If I go out [travelling], I make for 2 weeks. I have another one readily available if I

run out” [P4]. Many patients found pillboxes and blister packages useful in helping them take

their medications on time because it organized multiple medications into compartments

according to the time of the day: “Blister pack contains the meds for everyday and for what time

of the day. It’s divided into AM and PM. I tear off the seal for when I want to take my meds for

a specific time” [P3]. In many cases, medication adherence improved for patients who had their

complex medication regimen organized: “I get the bubble package with my pills. I used to forget

to take them. Once I was on insulin, the doctor recommended me to take the blister packs. I

might forget taking medications for a moment, but not for the day” [P6].

Proposed Features – Subtheme C1

Attaining a routine is key to setting a foundation for self-management [20]. Therefore the

mobile application should guide patients through tasks such as completing their measurements

and taking their medications based on certain established schedules determined by

43

clinician/patient preferences. Having consistent times may reduce the cognitive demands of

having to remember to take self-management actions [86]. Additionally, the mobile application

should have a reminder system to help patients remember to carry out self-management

activities.

Subtheme C2: Lack of proper resources to streamline record keeping.

It was observed that patients had loose pieces of papers containing items such as list of

medications, health conditions, measurements, and some had a mix of electronic and paper

records which they carried with them to their clinic appointments. Some patients encountered

problems keeping proper record of their measurements: “But to take a record is frustrating. I take

blood sugar, but it’s missing. [Patient shows her blood sugar logbook]. I took the reading and

didn’t put it right away for any reason, and I really don’t know what it was. It’s missing” [P4].

Some patients did not know their medical history well, such as one 83-year-old patient who was

unsure whether he had COPD and HF, although his medical files stated so. He was aware he had

been taking medications for a heart condition and had difficulties breathing at times, but the

patient had multiple chronic conditions and seemed unaware of which ones he had. Several

patients had medication lists on pieces of paper, either hand-written or typed themselves, or a

printout from the pharmacy or a clinic. Pieces of paper would state the medication names, dosage

and at times some description or purpose of the medication. One tech-savvy patient had his

medication list typed up as a note in his Blackberry phone, organized by the time of the day he

had to take his medications, “I’ve got them listed as AM and PM” [P14]. He used this list to

organize his pillboxes bi-weekly. Additionally, patients’ health information was scattered across

different providers and facilities: “I’ve got multiple doctors for medications” [P10].


A centralized information system that enables patients to consolidate, store and manage their

personal health information may be useful for patients. Therefore the mobile application

should provide means for patients to keep track of their measurements such as blood glucose,

blood pressure and weight through one system. The application should also provide patients with

a method of keeping a history of health related events as well as keep record of their

medications. This way the patients will need to rely less on messy notes and complicated diaries,

44

and instead have a streamlined record of their information that is quickly and conveniently

accessible.

Subtheme C3: Involve patients in maintaining an updated medications list.

Given that the presence of multiple chronic health conditions creates management difficulties,

clinicians have identified conflicting medications to be a common source of problem that can

lead to medication errors or inappropriate use of medicines. Sometimes specialists do not get

medication updates from the family doctors: “This way we are unaware of what medication the

patient is taking, because specialists send letters to family doctors, however family doctors don’t

send letters to us” [C1]. At the same time, primary care physicians expressed that they also do

not get updated on medication changes: “Ideally I would get a consultation note from the

specialist outlining the changes in the medications. It doesn’t always happen or not in a timely

fashion” [C2]. To resolve this situation, clinicians expressed that having patient involvement in

maintaining their medication list would be useful: “Any other physician can make changes and

we can't say "no" to the changes. We make the patients become their own case managers and

ask the patient to notify the CKD clinic of changes to their medications. CKD clinic doesn't get

notified from primary care physicians or dentists, etc. We put the responsibility on the patient”

[C1]. Primary care clinicians also expressed that the smartphone application could be helpful in

informing them that there were changes in the medications, “it has the potential to keep updated

with meds” [C7] and “if we can include medication and dose in a real-time update, I’ll find that

helpful” [C2].


The mobile application should help the patients maintain an updated and accurate list of

medications. The patients would not be making the changes to the medication list on the mobile

application because that type of responsibility should lay with a clinician who has expertise in

this field. However, the mobile application should enable patients to note that there was a

medication change, and a clinician such as a case manager from the primary care clinic can

verify the change with other care providers. Additionally, a time stamp and the name of the

clinician who made the last update should be stated at the top of the medications page of the

mobile application. A primary care physician mirrored this idea: “Even if the note says that the

45

medication was changed, it doesn’t necessarily include the dose. Sometimes I’ll know a

medication was added but not the dose. So if we can include medication and dose in a real-time

update, I’ll find that helpful” [C2].

Theme D: Provide resources to reduce conflicting advice.

Caring for patients with multiple chronic health conditions is complex. These patients usually see

multiple healthcare providers, and the different healthcare providers have different treatment

preferences based on what they consider to be more important. Moreover, there is a lack of

established guidelines for clinicians to follow in providing care for different combinations of

health conditions. Therefore, there is a need for resources that can help reduce conflicting advice.

Subtheme D1: Patients may receive conflicting advice from different clinicians.

Clinicians identified conflicting advice as one of the main challenges while providing care for

MCC patients. Conflicting advice makes it difficult for patients to know which information they

should follow and this could contribute to patients not following any advice or following

inappropriate advice: “How we deal with diuretics is very different. HF clinic would dose very

aggressively. We however won’t because it will make the kidneys dry up too much…In those

cases, between HF and CKD clinics, we have to determine who is taking over. If HF takes over,

then CKD won't touch the diuretic medications. We have fair amounts of those types of patients.

Even conflicting advice about diet – healthy heart diet would say to eat whole wheat and

incorporate fruits and vegetables. In contrast, CKD requires white everything, no fruits, no

vegetables. Patients are left confused. What are we supposed to follow?” [C1]

Multiple clinicians explained, “In the absence of trying to find the grand solution, it comes down

to what is the most dominant disease. It depends on the disease that is most active and most

dominant in terms of the patient’s profile” [C3]. Clinicians identified that targets for patients

need to be adjusted at times: “Good example for HF, we get to adjust their diuretics based on

their weights. That is sort of an empowering thing that we love to get to, because if we can, it

gives them the sense of being able to manage things. Frankly, it works out better for the patient”

[C4].

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Proposed Features – Subtheme D1

There seem to be various approaches to managing multiple chronic conditions. One approach is

to determine which disease is most dominant and prioritize the treatment of that disease.

However, clinicians also identified that targets for the parameters need to be adjusted based on

the changes in patients’ health status. Therefore, the mobile application should help monitor

specific parameters and enable clinicians to view and adjust the target ranges of the

parameters based on how the patient responds to the treatments. This would ensure the app is

customized to each individual patient’s care needs.

Subtheme D2: Lack of evidence-based guidelines for multiple chronic conditions.

Clinicians pointed out that there is a lack of proper guidelines for management of MCC, and

often things are done by trial and error: “I do see the benefit of managing these diseases. The

problem is that we look at all the guidelines and that they have been written in isolation from

each other” [C2]. Treatment for one disease could cause problems with another: “What I find

challenging is that there is good evidence what to do with HF patient, what to do with COPD

patient. Then you get this grey zone, when you have interacting diseases. Treatment for one may

make the other one worse” [C2].

Clinicians recognized the need for interventions for chronic condition management need to better

manage multimorbidity rather than single disease states: “Multisystem disease is the way of the

future. When you look at the group where HF is diagnosed, which is the elderly, many of them

have other comorbid conditions. Trying to do something isolated to one condition is probably

less applicable across the broad population” [C3].

Proposed Features – Subtheme D2

Predominant focus of medical guidelines has been on management of single conditions. Taking

into account that there are no fully developed guidelines in place for the multiple chronic

conditions indicated that there was no set of concrete rules or guidelines that the mobile

application could follow. For long-term, a large-scale framework by the healthcare systems is

needed to create evidence-based guidelines for management of various combinations of

chronic conditions.

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Theme E: Make appropriate use of the large amount of collected data.

Large amounts of data will be collected overtime, and it is important to present the data so that it

is easy to understand, without it being cognitively too difficult and time consuming to interpret.

Subtheme E1: Clinicians have limited time to review all data.

Patients with MCC could potentially be collecting multiple different parameters over time;

glucose for diabetes, blood pressure for hypertension, weight for HF, symptoms for various

different health conditions. Clinicians stated that they would prefer to get a summarized history:

“…a summary would be useful. Patients are so used to the healthcare system and know that they

can't generate these printouts, patients will often come with their own logs, history; you'd be

surprised what patients have come up with to track this” [C4]. As one clinician expressed, “it

would be really helpful to have a history of alerts. From just a medication standpoint, when I first

see a patient it is all about trying to get a history of the past 10 years and that takes me an hour”

[C7].

Proposed Features – Subtheme E1

Taking into consideration that clinicians may have only 15-20 minutes per patient, the mobile

application should present the data so that it does not take clinicians too much time to interpret

the data. The mobile application should provide interpretation of the data or summaries of

the data where possible to save clinician time reviewing patient history.

Subtheme E2: Graphical trends demonstrate changes overtime.

Clinicians indicated that graphical trends will be helpful for patients and clinicians in

understanding the patient’s progress overtime: “If they can also see their creatinine going up as

well, maybe they can get a better understanding of what it means rather than ‘your kidney

function 30% or its 50%’. Seeing that graphically will be helpful” [C5]. Observing trends would

be beneficial in making adjustments to self-management activities, “If it’s a diabetic who is

overweight and we are working on weight loss, it may be useful to trend that weight loss. If they

are gaining weight…we may have to be aggressive with lifestyle changes. Help them eat a bit

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more healthy” [P4]. Some patients also found graphical trends to provide a clearer picture of

their health status overtime, “I have a graph of my 100 days. Numbers by themselves are

meaningless but trends let me know what is going on. I’ve noticed certain foods like rice that

causes a spike” [P14].

Proposed Features – Subtheme E2

The mobile application should provide a graphical view of the data points that patients

collect so that they can visualize the changes overtime.

Theme F: Alerting system must be used appropriately.

Clinicians expressed interest in being notified about a patient’s condition so that corrective

actions could be taken to prevent worsening in their health status. However, concerns were

expressed regarding the time commitments and responsibility of ensuring the alerts were dealt

with appropriately.

Subtheme F1: Alerts enable clinicians and patients to be proactive.

Clinicians provided positive responses to having a remote monitoring system with an automatic

real-time alerting system that would notify healthcare professionals of deterioration in a patient’s

condition: “Alerts will be useful for me, ideally preventing hospitalizations and visits to the

emerg” [C3]. Other physicians shared similar sentiments of alerts being useful, “Measuring of

vitals and weight and have alerts when we are concerned, for example for increased weight gain

or blood pressure elevations that would be useful” [C2]. Alerts would enable clinicians to be

proactive instead of reactive to the patient’s conditions: “By getting alerts – by getting patients to

report ahead of time of what is actually happening to them will help us be more proactive so that

we are not always trying to catch up with what has already happened” [C4].

Proposed Features – Subtheme F1

The mobile application should have a mechanism to alert the clinicians, which could

substantially shorten the time to address problems that may arise.

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Subtheme F2: Need to determine which clinician must be monitoring alerts.

There was difference in opinions of whether the alerts should be sent to all healthcare providers

involved in a patient’s care or just to a clinician in primary care. More than one clinician stated

that if alerts were sent to many clinicians, then there would be a question of whose responsibility

is it to take care of the alert. The importance of the alert will diminish: “Shared responsibility. If

we know that the alerts are only coming to us, as primary care physicians, then maybe we would

avoid that. Versus if it goes to everyone, we might say that someone is doing something about it”

[C4]. Another clinician who had worked with RPM systems previously also stated the same

issue: “The more people things get sent to, the less responsibility any one person feels over it”

[C3].

The clinician elaborated that for an alerting system to work efficiently: “There should always be

an MRP, most responsible physician. Maybe that person is a nurse practitioner and sees that it’s

an alert for creatinine is in the 800. She knows to go to the nephrologist. And if the alert is that

the patient blacked out, then she knows she should go to the cardiologist. You need that point

person who could actually triage whatever the symptom is and send it to the right person” [C3].

Figuring out the workflow of the clinics is important in order to for the alerting system to work

efficiently. One primary care physician clarified their clinic has physicians that are on-call and

alerts generated through mobile application “will just replace one sort of workflow with another.

So instead of getting phone calls from the patients, I’ll get alerts from those patients” [C2].


In order for the alerting system to work efficiently, it would be critical to have a clinician who

can direct alerts to the most responsible person for that issue, with notification to the other

clinicians involved in the care.

Subtheme F3: Alerting system must not disrupt clinicians’ current workflow.

Clinicians were supportive of the alerting system however they did express some barriers that

would prevent them from working with the system, one being time commitment required to

monitor the alerts: “I worry a lot about when the alerts will get sent and if this is going to happen

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in business hours or outside business hours. What happens when they feel symptoms at 3am? I

have lots of concerns about separating my work and my personal time” [C3]. The same issue was

also mentioned by another primary care physician: “It will be essentially like giving our

cellphone number to every patient you have and they call whenever. I don’t think for myself that

would work. There may be some people who would be okay with that. Personally I’m not” [C4].

Furthermore, there is a lack of proper financial reimbursements for alerts being monitored by

individual clinicians on their own time: “ There is no funding attached to this. I answer between

15-20 emails a day to my patients. There is no reimbursement of any kind. I’m fine with that,

because that’s not what drives me. But if we want this to be taken up more broadly in the

community, then a family doctor with 500 complex patients will need to take real time; and if

you don’t enumerate this in some way, I don’t know how you think it’s going to be done” [C3]. Additionally, having too many alerts being sent to the clinician will cause alert fatigue as

expressed by a clinician: “I just worry that there will be so many alerts and triggers that it will

lose meaning” [C3].


The app should ensure that the algorithms for generating alerts that are being sent to clinicians

are useful: “It will be more useful to have triggers that are critical, so those that are quite low or

quite high” [C4]. A hierarchy of alerts should be created, with the intention that the more

critical alerts would be being sent to the clinicians. The less critical alerts generated by the

app should only be sent to the patient so that they can be made aware of their health status and

take corrective actions.

Theme G: Establish efficient communication

Patients with multiple chronic conditions often need to meet with multiple healthcare providers.

This complicates their care pathway and is a cause for inefficient exchange of information

among patients and clinicians. Not only are communication pathways to and back from the

patient limited, but also another overarching complaint from the clinician interviews was the

inefficient inter-clinician communication. Therefore a system that can aid in seamless

communication would be very helpful in providing coordinated care to the patients.

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Subtheme G1: Patients have difficulties making visits to multiple doctors.

Self-management of drugs, treatments, and medical appointments were perceived as being

difficult, and complicated access to the healthcare system simply intensified the experience

associated with having multiple chronic conditions. Some patients expressed dissatisfaction with

accessing their healthcare providers due to difficulties getting to their appointments: “I live in [a

suburban area]. I don’t drive. I have to worry about getting here. So I don’t come here [to the

clinic] as often as other people. I should be coming four times a year, but I come once or twice”

[P6]. Some patients expressed their dissatisfaction with difficulties getting appointments with

their doctors and long wait times for their appointments: “I have been seeing [the family doctor]

for 11 years. When this clinic opened, you could get an appointment within moments. But now

there are 10,000 patients.” [P9]

Clinicians also recognized that having multiple care providers could be a factor in patients

missing some appointments: “To be honest, we often have patients with huge number of

specialists. I’d like to see them every 3 months, but it may not be happening. They have some

specialists they see every so often. We will actually not end up seeing them and we end up

relying on information that is sent back to us” [C4]. However, to provide a better picture of the

patient’s health status, it would be useful to have patients share their information: “Symptoms,

blood pressure – everything. The answer is everything because if I only have part of their puzzle

then it’s hard for me to put things together. I need to know their symptoms. I need to know their

vital signs. I need their active medication list. Maybe they’d be more interested in this so that

they can come to the office less” [C3].

Proposed Features – Subtheme G1

System should enable patients to share their health information with their doctors through

the use of web-interfaces. A platform such Medly Dashboard could be utilized as a web user-

interface and server that are used for information exchange between multiple facets involved in a

patient’s care regimen.

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Subtheme G2: Communication is inefficient between multiple providers.

People with multiple chronic conditions often receive care from multiple clinicians, who may

work independently from each other. Each of the clinicians may provide one or more of the

services that comprise the full spectrum of care the patient needs, such as medical, mental health,

rehabilitation, prevention and supportive services. Most of the interviewed patients had the

impression that their clinicians were communicating efficiently with each other regarding the

patient’s care.

However, communication pathways between the different care providers were often suboptimal

as conveyed by multiple clinicians. Specialists wanted the family physicians to be aware of the

changes in the patients’ care plans: “The ideal is that they should be aware. Anytime there is a

change made to their care plan, medication, a letter is sent to their family physician, but in reality

how much the family physician really knows is not known. Sometimes the primary physician

contacts the CKD clinic again to ask about changes even though CKD clinic has already sent this

info. Patient comes back 3 months later, and there are lots of changes like they have pressed the

reset button. In an ideal situation, the family physician should be the center person, but they are

always in the periphery, which is not the ideal” [C1].

Similarly, family physicians were also displeased with the lack of proper communication with

the specialists: “It’s more useful if you can see what someone else has been thinking or what

they wanted to do, rather than trying to rely on the patient to relay that information to you; which

happens to us a lot. So you know, often I ask people what did the cardiologist tell you, and they

don’t know” [C4]. By functioning as separate entities, the clinics often do not have complete

information about the patient’s condition or treatment history.

Proposed Features – Subtheme G2

To meet their complex needs, patients with chronic conditions often receive care from multiple

clinicians, who may work independently from each other resulting in fragmented and poorly

coordinated care for the patients. Therefore, the system should enable healthcare providers to

have quick and secure availability to a central repository where data captured by patients

and related to the patients’ health conditions are held. Ideally an inter-clinician

communication system should be developed that facilitates communication between the

clinicians. One clinician added: “I try to add the [specialists' names] onto their charts” [C10]. In

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terms of this project, a page was created for the app with a list of the patient’s main care

providers and their contact information such as of their family doctors, specialists,

pharmacists and other health care providers involved in their health care so that clinical team

members can be contacted if and when necessary.

4.2 Phase II: Smartphone Application Design and Architecture

4.2.1 Comparison of Existing Apps

Interviews with patients and clinicians had provided a basis of what features would be

useful for self-management of multiple chronic conditions though a smartphone application.

Understanding the existing disease-specific apps had provided insight into how the features

could be designed. The smartphone application designed in this project aimed to provide a self-

management system for patients with multiple chronic conditions. This smartphone application

will hereby be referred to as the MCC app. This MCC app utilized the knowledge base that had

been established for previous disease-specific smartphone applications at the Centre for Global

eHealth Innovation. The key difference between the existing smartphone apps and the one that

was being created for this project was the fact that the existing apps focused on single chronic

conditions. These existing disease-specific apps had mainly been developed in collaboration with

tertiary clinics where patients had advanced level of severity in health conditions and required

more frequent monitoring. In contrast, there was much variance in the severity of patients’ health

conditions and level of monitoring and care required in the primary care clinics (as discussed

under Theme A in Section 4.1.2). Additionally, there were many differences in the features and

backend architecture of the disease-specific apps. Therefore, integrating algorithms and features

from these different apps to develop one integrated app for MCC was more complex than

originally understood at the start of the project. Comparison of existing features among the

disease-specific apps is shown in Table 4.

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Table 4: Comparison of features of existing disease-specific apps.

HF CKD COPD DM HTN

Blood Pressure (BP) ✔ ✔ ✔ Heart Rate ✔ Weight ✔ Blood Glucose (BG) ✔ Symptoms ✔ ✔ ✔ Lab Results (K, P, Hb) ✔ Context for Measurements ✔ (morning/later) ✔ (mealtime) Alerts ✔ ✔ ✔ ✔ ✔ Trend Review ✔ Graphs of Measurements ✔ (weight) ✔ (BP & Labs) Table of Measurements ✔ (BP & Labs) Timeline of Events ✔ Medications List ✔ ✔ Flare-up Medications ✔ Medication Reminders ✔ ✔ Internal App Reminders ✔ ✔ External App Reminders ✔ Calendar ✔ Care Team Info ✔ Training Videos ✔

Different designs and architecture of the MCC app and its contents were explored, utilizing the

information gathered from interviews with patients and clinicians and understanding of the

architectures of the existing smartphone applications. Detailed comparison of the features listed

in Table 4 demonstrated that there were many issues to resolve in order for some of the features

to be leveraged for an integrated MCC application.

Symptoms Questions

Symptoms questions were asked in the smartphone applications of three chronic conditions:

COPD, HF and CKD. There were 6 – 11 questions asked within the HF application and

consultations with a HF specialist reconfirmed that these questions should continue to be asked

for HF patients. The COPD and CKD questions were already recently validated while the MCC

project was in the early phases of design. CKD and HF apps simply asked patients to respond yes

versus no to the symptoms questions. The COPD app asked yes versus no, but also asked about

severity of the symptoms (i.e. yes, a little; yes, moderate; yes, a lot). All three apps had different

55

methods of inputting responses to the symptoms questions. The HF app was more interactive and

the questions were full sentences. The CKD and COPD app asked short statements.

Table 5: Comparison of symptoms questions in disease-specific smartphone applications.

COPD HF CKD Type of Answers Yes (a little, a lot), No

Yes, No Yes, No

Number of Questions

6

6 – 11 (dependent on previous answers)

5

Frequency of Questions

Every day, preferably in the morning. Questions reflect symptoms the patient had in past 24 hours

Typically every morning, but can enter anytime during the day when patient is experiencing any symptoms

Every other day and monthly (dependent on severity of illness)

Contextualization None Identify symptoms as morning / extra reading

None

The main issues among the symptoms questions were: (1) some of the questions were similar so

they needed to be combined somehow to prevent repetitiveness; (2) questions for COPD were

referring to symptoms experienced in past 24 hours whereas CKD and HF questions were asking

patients about symptoms being experienced at the moment; (3) contextualization of HF questions

was necessary in order for HF algorithm to function whereas it was unnecessary for CKD and

COPD; and (4) the design of presenting and responding to symptoms was different. This project

was able to identify issues in combining the symptoms questions for various combinations of

chronic conditions and methods to resolve these issues were explored. However, additional work

is needed to resolve these issues. It should be noted that changes in the symptoms questions

would also affect the pre-existing algorithms that have been developed and stored in the Medly

system, and thus the effects of symptoms’ responses in combination of disease-specific

algorithms should be further investigated to create an integrated solution

Alert Algorithms

This MCC app leveraged algorithms and content from previously developed telemonitoring apps

which had been vetted by specialists and were being evaluated at various stages of clinical trials.

The HF algorithm was re-evaluated by a cardiologist at UHN who was involved in the original

study. The HF alerts algorithm remained the same as the ones used in the original study by Seto

et al. [12]. The COPD algorithm was developed in collaboration with Asthma and Airway

Centre at UHN, and the algorithm remained the same for the MCC project. However, for this

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project the severity levels of COPD algorithm were recoded in order to make them parallel to the

HF hierarchy of alerts. The DM algorithm was re-validated by a diabetes specialist at UHN.

Consultations with the diabetes specialists lead to changes in blood glucose target ranges for

generating alerts, as well as some changes in the content of the messages. The HTN algorithm

had two components: (1) alerts and feedback on whether recorded blood pressure readings are

within controlled range and (2) trend alert if blood pressure readings have been repeatedly high

or low. Both the alerts and trend algorithms were created based on discussions with a

hypertension specialist. The CKD app’s blood pressure algorithm was leveraged to generate

alerts based on two sets of blood pressure readings. The concept of trend reviews from the DM

algorithm was used to develop an algorithm to generate trend review alert after 5 days of

repeatedly high or low blood pressure readings. Taking the design principle of consistency into

consideration however, the days in the blood pressure algorithm could be consistent with the DM

app so that patients do not need to remember that their blood glucose trend alert is triggered after

3 days but their blood pressure trend alert is triggered after 5 days.

Trend Review Wizard for Blood Pressure – New Feature

The trend review system for blood pressure readings utilized the architecture from the DM app

which generated trend review alerts if repeatedly high or low readings had been recorded. The

DM app was based on the blood glucose readings being contextualized based on mealtimes ex.

breakfast, lunch, dinner, overnight. So if three days of repeatedly high blood glucose readings

had been recorded during breakfast time, then the user would be prompted to complete a trend

review to understand the causes and fixes for high blood glucose readings. In contrast, blood

pressure did not depend on mealtimes. Instead it was thought that if 70% of the blood pressure

readings in one day were high, and 70% of the readings continued to high for next five days, then

a trend review alert would be triggered (Figure 4). The 70% rule was utilized to take into

consideration that during a day, incorrect blood pressure readings may be recorded due to

improper use of equipment. This would skew the average of the day. Thus the logic was that if a

majority of the readings in a day were repeatedly high or repeatedly low then that day was

recorded as high or low respectively.

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Figure 4: Blood pressure trend review algorithm utilizing 70% rule.

However, because the 70% rule had not been tested before, after consultations with a

hypertension specialist, it was decided that using averages for each day would be more suitable.

So if the average of each of the five days were repeatedly high or low, then a trend review would

be triggered. The trend review page for blood pressure that has been developed for the first

version of MCC app showing the original list of causes and fixes is displayed in Table 6.

Table 6: Scrollable trend review page content for blood pressure.

Original List of Causes and Fixes Most Updated List of Factors

List of factors by level of importance. 1. Forgot to take medication 2. Poor eating habits 3. Too much salt 4. Change in weight 5. Not enough exercise 6. Poor/disturbed sleep 7. Excess alcohol intake 8. Other

• Caffeine • Recent travel • Recent illness • Over-the-counter drugs • Herbal remedies • Recent hospitalization

Hypertension Canada Guidelines and National Institute for Health and Care Excellence (NICE)

guidelines for hypertension as well as consultations with a hypertension specialist lead to

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iterative changes in the list of causes and fixes, with the most updated list of factors displayed in

Table 6. The most updated list of factors has not been integrated into the MCC app, because

further design work and development time would have been required. The possibility of having

open text was also considered to enable users to add in their own reasons for what they believed

could be factors affecting blood pressure, such as stress, work, family, etc. However, it was

suggested by the hypertension specialist that in order to improve patient awareness of the actual

factors that may be affecting the blood pressure, it would be better to have the list of factors

shown in Table 6 (i.e. most updated list of factors) with links to the clinic’s websites or proper

sources (validated by the clinicians) of how those factors affect blood pressure and how to

mediate the problems. Therefore the trend review component for blood pressure should be

explored further to ensure it complies with the clinical advice.

Medications Page

Architecture for medication list integration was also explored. A pharmacist from the family

health team provided great insight into the medications page of the app. She provided a sample

medications page that would be given to the patients at the family clinic, particularly the patients

with multiple health conditions who were taking several medications per day. She suggested

dividing the medication list by “morning, lunch, dinner and bedtime” and allowing a clinician to

select which lists needs to be populated. Considering that patients during the semi-structured

interviews had also organized their medications into pillboxes based on daytime, such as using

AM versus PM containers, it may be better method to display the medications list. During the

semi-structured interviews, it was also observed that patients often times had their hand-written

or printed medications list divided by time of day.

Another item of discussion with the pharmacist was of the idea of dividing medication lists based

on whether it is needed regularly or when there is increase in severity of symptoms, such as an

exacerbation of COPD due to excessive air pollution. The COPD app had a medications page

that has two tabs: Baseline and Flare-Ups. The Baseline tab contained medications that the

patient had to take on a daily basis, whereas the Flare-Up medications were those the patient had

to take during an exacerbation. For HF, patients may take a diuretic called Lasix for example that

is similar to the concept of a COPD flare-up medication. Brainstorming on proper names of tabs

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to differentiate between ‘daily vs. as-needed’ medications produced a couple options that could

be considered for future use for development of medications page for multiple chronic

conditions.

Further issues that were identified during comparison of the features among the disease-specific

smartphone applications are shown in Table 7. Some issues were resolved and some need to be

explored further for future iterations of the MCC app.

Table 7: Comparison of existing smartphone applications and issues that needed to be resolved. Issue # Issues Arising in Disease-Specific

Apps Actions taken for development of MCC App

Issue #1 – Patients needed a modular app

It was clear during the interviews that the MCC self-management must be modular. • Although some of the parameters

were similar among the disease-specific apps, there were many differences that made it difficult to simply put components together. For instance, disease-specific algorithms could end up providing contradicting alerts and notifications. Example: Blood pressure readings were dealt with differently for CKD, HF and HTN.

à Determined changes required for adapting the content of existing apps to create an integrative MCC app for primary care population. (Subtheme A1) à Ensured that the MCC app is modular so that parameters would be displayed based on the chronic conditions selected on the smartphone. (Subtheme A1) à Was unable to link the MCC app to Medly Dashboard for this project due to time constraints. In future, clinician should be able to select conditions on the Dashboard and the MCC app will configure itself to that selection. (Subtheme G1)

Issue #2 - One reading would transfer into multiple apps

User would be required to launch disease-specific apps for notifications related to the same measured parameters. Example: Blood pressure notifications would occur in both CKD and HF apps, and user would be required to launch two different apps to read two different notifications.

à Ensured that when one measurement is transferred to the smartphone, it is dealt with appropriately in one integrated app despite being used for two different chronic conditions. (Subthemes A1, B1)

Issue #3 - Algorithms were based on tertiary clinics

The disease-specific apps had been developed with specialized tertiary clinics and were geared towards patients with more advanced level of chronic conditions. • However, in the interviews with

primary care patients it was realized that there is a wide range in severity of health conditions, and many of those visiting primary care have milder forms of conditions.

à Re-validated disease-specific algorithms and validated the new algorithms by clinicians. Then resolved the different algorithms so that they could work in any combination of the diseases. Further testing should be performed to ensure they function properly. (Subtheme A1, A2) à Used a set schedule for the current development of MCC app v1.0 to get it ready for testing. However, in the future clinicians should be able to select how frequently they want the patients to perform certain measurements. (Subtheme A2)

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à In the future, instead of having disease-specific algorithms, maybe it would worth trying to ensure individual parameters are being managed well.

Issue #4 - Alerts and notifications displays were inconsistent

Alerts and notifications were displayed differently across the different apps. There was also variance in the tone of the language and type of content of alerts.

à Ensured all alerts and notifications were displayed in a consistent manner. Ensured the content utilized similar tone and style of language. Further work may be needed for improving overall tone of the MCC app. (Theme F)

Issue #5 - Alerts were dependent on connection to servers

Some alert algorithms were stored on the servers, so alerts could not be generated on the phone if there was not a strong internet or Wi-Fi connection available on the smartphone.

à Developed the MCC app so that the algorithm run on the phone and therefore the user will receive alert messages without needing to be connected to servers. (Theme F)

Issue #6 - Too many symptoms questions

There was variance in the symptoms questions being asked in the CKD, COPD and HF apps, resulting in >20 questions altogether, albeit some being similar.

à Determined which questions could be omitted to create a shorter list of questions for different combinations of conditions. Consulted with clinicians regarding symptoms questions that were most necessary to include in the app. (Subtheme A1)

Issue #7 - Variance in symptoms questions

There is variance in the sentence fragments and context of the symptoms questions being asked, as well as in the style that user is required to respond to the questions.

à Explored best methods for displaying and responding to symptoms questions.

Issue #8 - Variance in medication lists

Medications list requirements differed among conditions. Example: COPD has flare-up medications that are not to be taken on a daily basis but only during exacerbations.

à Explored most appropriate method for displaying medications that is applicable for any combination of chronic conditions chosen. Also considered the need allowing users to activate medication reminders. (Subtheme C3)

Issue #9 - Variance in graphical displays

Graphical displays between the parameters differed greatly. Example: DM app displayed colored data points based on mealtime (breakfast, lunch, etc.). In contrast, CKD app displayed data points based on severity (yellow=bad, white=good). Example: Data values exceeding the vertical (y-axis) scale range would not be displayed on the graph or would be displayed at the very edge of the graph. Autoscaling was another option, which meant the vertical scale would automatically readjust to fit all data.

à Explored designs to ensure graphical displays were consistent throughout all parameters. Need designer input in the future to further resolve all issues. (Theme E)

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4.2.2 Design Principles

Information gathered from the semi-structured interviews and analyzing of individual

smartphone applications provided insight into design principles for the Medly system for

multiple chronic conditions. The design principles were finalized through an iterative process, on

the basis of discussions with members of the committee and the PHIT team.

Table 8: Findings and resultant design principles.

Findings Design Principles Different combinations of multiple chronic conditions required monitoring of different health parameters.

System should be modular, so that components can be added or removed according to the needs of the patient.

Patients had varying needs for monitoring: no monitoring, some monitoring and daily monitoring. Some algorithms in existing single conditions applications are dependent on daily monitoring.

System should accommodate for patients with varying needs of monitoring. Algorithms should be modified to accommodate patients who do not require frequent measurements.

Patient adherence to positive health actions improves when they have established routines.

System should help patients establish a routine. Reminders should be utilized to prompt patients to perform telemonitoring actions according to schedule.

Patients may have health conditions that have conflicting best self-care practices. Inappropriate advice should not be given that would cause exacerbation of their other conditions.

System should provide appropriate feedback according to the combination of health conditions and various levels of severity. Content of the system should be validated by clinicians, including the algorithms and messages of the alerts and notifications.

Many patients had limited experience with using smartphone technology.

System should be intuitive and provide easy navigation and guidance to the patients.

Establishing connection between external devices and the smartphone was sometimes complicated.

System should have a reliable method for establishing connections between smartphone and external devices. Appropriate guidance should be provided for troubleshooting.

Patients lacked proper methods of consolidating health related information, such as medications list, diagnoses and contact information for their health care providers.

System should streamline record keeping of pertinent health related information.

It is cognitively difficult and time consuming to interpret large amounts of numerical data that has been collected over time.

System should provide meaningful summaries, graphs or interpretation of the data to help patients and clinicians see patterns overtime and take appropriate actions.

Clinicians were concerned about managing alerts and the disruption to their workflows and routines.

System should fit within the existing workflows of the clinics. Alerts generated for different health conditions should be dealt with appropriately, as determined by clinicians.

Communication between multiple healthcare providers was inefficient.

System should have a central repository for clinicians to access data collected by the patients, as well as other health related information.

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4.3 Usability Testing Round #1

4.3.1 Scenarios and Prototype Designs

Prototype designs used for this round of testing were based on features determined through

formative interviews with patients and clinicians in Phase I. Some sample designs used for the

first round of usability testing are shown in Figures 5 and 6.

(a) Main Page – contains a checklist of measurements. Uncompleted items contain the icon. Completed items receive a color-coded checkmark i.e. red = out-of-range, green = normal.

(b) Alerts – are at the bottom of the screen along with the parameters that are responsible for generating that alert to appear.

(c) Immediate Feedback – for each measurement the user takes

Figure 5: Screenshots from 1st set of designs of MCC app used in Usability Testing Round 1.

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(a) Main Page - contains a list of measurements to take. Added the menu buttons at the bottom of the page to provide easy navigation for the users. Improved the symptoms button to enable users to record and update their symptoms.

(b) Alerts - moved to top of the page. Measured values are available on the main page to validate to the user that the reading has transferred from the external device to the smartphone.

(c) Immediate Feedback – more information available about the reading is available if the user taps on the the ‘information’ icon in top right corner.

Figure 6: Screenshots from 2nd set of designs of MCC app used in Usability Testing Round 1.


First round of usability testing was conducted with 6 patients and 4 clinicians. Usability testing

with patients was conducted over a 2-month period (November – December 2014). The patient

participants were the same as those the study coordinator met for formative interviews. As

shown in Table 9, the patients had different combinations of chronic health conditions, and

altogether they encompassed all five chronic conditions that were part of the research project:

HF, COPD, CKD, HTN and DM.

As shown in Table 10, half the patients did not own a smartphone. Of the three patients who did

own a smartphone, they either had an iPhone, Android or a Blackberry. The Android user was

somewhat comfortable using the phone, and his use of the phone extended to voice calls and

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texting his grandchildren. The other two smartphone owners were more comfortable using their

phones, which they used for more advanced functions such as emailing, scheduling and

information seeking. The remaining three patients had cellphones, which they did not use

frequently and mainly for voice calls and texting. Most of the patients had a laptop or computer

at home but the frequency of its usage varied. These traits indicated that there is a variance in

the user population in terms of familiarity with technology, from some being quite tech-savvy to

some using their cellphones, smartphones and computers very minimally. Lastly, all patients

required reading glasses, with half of them also requiring distant glasses. This indicated that the

size of the content on the screens would need to accommodate for users with declining vision.

Table 9: Patient demographics for Usability Testing Round 1.

Characteristics

N (n = 6)

Age 18 – 39 years old 0 40 – 64 years old 2 >65 years old 4



Elementary 0 High School 3 College/Undergraduate 2 Post-Graduate 1


Hypertension + Diabetes (Oral Meds) 1 HF + COPD + Diabetes (Oral Meds) 1 HF + Hypertension + Diabetes (insulin) 2 CKD + Hypertension + Diabetes (Oral Meds) 1

Table 10: Patients’ technology-related characteristics for Usability Testing Round 1.

Total (n=6)

N




What type of smartphone do you use? Blackberry 1 iPhone 1 Android 1


Frequently (few times a day) 2 Sometimes (few times a week) 1 Rarely (few times a month) - Never -


Voice calls 3 Text messaging 3 Email 2 Information seeking 2

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Scheduling 3 Information storage (e.g. contacts) 3 Other -



Very comfortable 1 Comfortable - Somewhat comfortable 1 Not comfortable 1


Frequently (few times a day) - Sometimes (few times a week) 1 Rarely (few times a month) 1 Never 1





Frequently (few times a day) 1 Sometimes (few times a week) 3 Rarely (few times a month) - Never 1



Distance 0 Reading 3 Reading and Distance 3

Three of the clinicians recruited for the first round of usability testing were from primary care

clinics, with one of them being the same as those met for semi-structured interviews. One of the

primary care clinicians was a physician, two were nurses and one was a pharmacist from family

health team. The fifth clinician was a specialist from the CKD clinic with specialization in

hypertension. Clinicians were recruited over the span of 3 months (November 2014 – January

2015). Usability sessions with each of the patient and clinician participants lasted around 30

minutes.

4.3.3 Results from Usability Testing Round #1

Reduce Swiping

It was observed during the usability sessions that most of the patients were not familiar with

using the smartphones and the older population was not used to touchscreen. Some of the Medly

apps that required swiping were difficult for the users to use. Even the patient with the

Blackberry commented: “Not used to swiping yet. I thought touching one of the buttons down

there would work. It’s good enough. I’ll figure it out eventually” because his Blackberry model

was not touchscreen. Overall, tapping buttons was a more familiar action for the patients, so they

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were pressing down on the touchscreen with varying pressures. But even that was a difficult

action for a few. Therefore, the designs of the app should minimize actions that require

swiping and focus on providing navigation through the app through tapping.

Reposition the Alert Messages

During the usability test sessions with the first three patients, the alerts were listed at the bottom

of the main page, below the checklist of actions items. It was quickly realized that the users did

not pay much attention to the alerts when it was positioned this way. Considering that the alerts

were crucial features of the app, needed to prevent further deterioration of patient's health, it was

necessary to improve the visibility of the alerts. Therefore, the main page of the app was

redesigned. The alerts were moved from bottom of the page to the top of the page (Figure

6b), so that they would get noticed and were paid attention to.

Restructure Display of Alert Parameters

Displaying alerts for HF was most complicated, because HF alerts were dependent on more than

one parameter: symptoms, weight and blood pressure. In comparison, DM alerts were based on

individual blood glucose readings and it was much simpler to provide an explanation to the user

for why an alert was generated, "Critically High Blood Sugar, 26.2 mmol/L". For a patient with

HF for example, if they first recorded abnormal symptoms, the alert for symptoms would be

listed first. Then if the patient recorded abnormal weight, the alert for that would be listed

second. Next, if they measured blood pressure, they would be notified of high blood pressure. On

the main page of the app, these individual alerts would be rearranged to indicate to the users that

a HF alert was generated due to: high weight gain, low blood pressure and abnormal symptoms.

One user said 'I like the grouping of the information. I like that it is not too wordy" [P10].

However, this user and others alike did not realize that the grouped information was related to

the HF alert message "Take extra Lasix as recommended by your doctor" displayed right above

(shown in Figure 5b). Therefore, the presentation of alerts and its related parameters

needed to be rethought. Multiple designs were explored to overcome this issue, as shown in

Appendix A.

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Improve Navigation to Features

The target populations of the app are people with multiple chronic health conditions, who tend to

be older and low users of newer technologies such as smartphones. They click on items that is

easily visible on the screen. So for this set of users, the app should not have too much hidden

information and it should not have too many layers of information. During the usability sessions,

the older patients were not aware of how to navigate away from the main page and access other

features of the app such as medications list and trends page because these features were listed

off-screen behind navigation drawer (hamburger) icon in the top corner. Therefore, a tab bar

containing five of the main features of the app was added onto bottom of the screen of the

app, as shown in Figures 6a and 6b. The tab bar was a row of persistently visible buttons that

opened different parts of the app. Navigation options were splayed out on the screen instead of

hiding in a drawer. This kept users from forgetting they existed and allowed rapid switching

between features without the need for the user to retreat back to the app’s home screen. The tab

bar received positive reviews with comments from patients such as, “I’m definitely impressed,

you do seem to be thinking in how I would be handling things” [P14].

Reinforce Content Using Words

It was observed that users would misinterpret or ignore certain symbols and colors. For example

one patient stated, "I didn't realize that the red indicated a high reading. Thought it was a brown

reading...Wondered why symptoms were red as well” [P14]. Another patient did not understand

the purpose of having an asterisk next to symptoms recorded, which was inherited from the

Medly HF app to indicate that abnormal symptoms had been recorded. The patient stated,

"asterisk 2 is not useful" [P10] referring to Figure 5b. Therefore, messages and content should

be reinforced with the use of words when possible.

Provide graphical displays and values of each recorded measurement

Patients expressed the need to view exact data values in order to determine how well they are

managing their parameter, such as blood glucose, at a particular moment. However, they also

found it useful to view trends to see how they have been doing overtime: “I actually have a

graph of it on my spreadsheet of when I started using insulin which shows that when I started

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using insulin there is a trend of decreasing blood glucose and then a plateau” [P13]. Therefore,

the app should provide patients with a graphical display of the measurements as well as the

exact values that were captured. Two different designs were explored. The first design covered

the full screen with a graphical plot of the data points and users could tap a button to switch to

view to a tabular format containing exact values, dates and times of measurements. The second

design also contained a graphical plot of the data point, but the users could tap on individual data

points to view the exact value of each individual data point.

Two patients who took daily blood sugar measurements expressed that it would be helpful for

them to see trends over time. One patient stated that he downloads his blood glucose values from

the glucometer and creates a graph on excel to see how he has been doing overtime. The patient

stated “I need to see trends for 7 days, 14 days, 90 days, and beyond” [P14]. Therefore, the

design of the app should consider having a feature that enables patients to select which

trend patients would like to view. A similar feature does exist in the Medly Diabetes app which

could be leveraged, whereby the user is able to view statistical summary of readings over 7, 14,

21 and 90 days.

Provide Capability to Set Medication Reminders

It would be beneficial for some patients to be able to set reminders that help them to remember

when to take their medications. Patients who have had been taking medications for a long time

did not find it challenging to take their medications. They had developed methods to keep track

of their medications through the use of pillboxes or blister packs and developed a daily routine to

take their medications morning, afternoon, evening as per recommendations of their doctors or

pharmacists. However, patients who were new to their diagnosed conditions or were leading

very busy lifestyles would find medication reminders useful. For example, one patient said,

“Remembering to take medications was challenging. I was on-call IT so it was a hectic life.

Reminders to take medications would have helped” [P10]. Another patient utilized his

Blackberry to remind him to take his insulin, “I have reminders for certain times I have to take

insulin” [P14]. Therefore, the app could provide patients with the capability to set

reminders to take their medications. This capability has been developed in the CKD app and

could be transferred over to the MCC app.

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Enable Activating or Deactivating of Reminders

Some users were less enthusiastic about the need for reminders. Patients who have been dealing

with their conditions for a longer period of time did not think it was important for them to have

reminders to take their measurements: “If I need reminders after this time, I’m stupid. When I get

up, I wash my face, I make coffee. I take coffee black so it doesn’t affect my blood glucose. I test

my blood glucose before I have anything to eat. I estimate what I’m going to be eating in terms

of grams of carbs. I need X amounts of insulin. Before I inject the insulin, I’ll have a fruit.

Before I have cereal or eggs or muffins, I’ll take my insulin before I do that. Lunch, same

routine. Check my blood before eating, then take insulin after I eat. Same thing I measure before

bedtime. COPD same thing. I brush my teeth and take my puffer. I shower at night. I’ll take my

puffer and brush my teeth. It’s a routine, I don’t need a reminder.” Therefore, the app should

allow users to activate or deactivate reminders to take their measurements, medications

and other tasks.

Have the Ability to Email and Print the Information Stored in the App

Patients liked the idea of keeping an electronic record on their phone but wanted the ability to

share their information with family members and care providers through email: “download the

readings into my computer, and then I can send them off to whoever.” [P15] Although our Medly

system provides access to patient data to the clinicians via the Medly Dashboard, it does not

provide the ability to share the patient’s data with other members involved in the patient’s care,

such as family members. Patient 12’s daughter was in the room during his visit to the clinic for

usability testing and she mentioned that it would be useful for her to be able to email the data so

she can print it and help her elderly father in his care. Some patients wanted the ability to print

out their medication list: “Unfortunately I don’t have a way of printing this [medication] list.”

[P14] Therefore, the app should enable users to email specific contents of the app in a format

such as .pdf or .txt so that they can make use of it accordingly. Therefore, the app could allow

users the option to email certain content stored on the phone to an email address.

Have Reminders Outside of the App for Recording Measurements

It would be beneficial for patients to be given reminders telling them to record their

measurements. A patient with COPD who had tried out the symptoms questions during the

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usability testing stated, “I would probably do the symptoms questions at the end of the day, with

the wrapping up of the day when I take my insulin. Would be nice to have reminders telling me

to record my symptoms. Alarms setting. Reminders to take symptoms and do measurements

everyday.” The patient elaborated that even without having the app opened, the app should send

a reminder to open the app and perform the required tasks, “… it wants me to answer

questionnaires once a day. It would be nice if it reminded me to do so. Reminders to run the app

everyday. Hopefully in the long run all this would be integrated, my meds could be on one alarm.

Time to do your stuff and go through all these things once. It might expand onto other conditions

as well. Possibilities are endless.” Therefore, the app could provide patients with the

capability to set reminders to take their measurements and the reminders should pop-up

external to the app.

Provide More Guidance in Completing Required Tasks

One of the clinicians said that showing “3 readings pending” on the main page of the app to

indicate that the patient still had some uncompleted measurements was not “intuitive”. He

suggested a “pop-up should show ‘now measure weight and blood pressure to go further’”. It

was also observed during the usability testing that patients were unsure what steps to take next.

The instructions at the top of the main page “Take your symptoms, weight, blood pressure and

blood glucose measurements today” were not sufficient. Therefore, the app should break

down the complete tasks and carry the patients through each task one by one. One clinician

described it as “hand-holding the patients through the actions they need to take”.

Content of the Medications Page

Another item of discussion with the pharmacist was of the idea of dividing medication lists based

on whether it is needed regularly or when there is increase in severity of symptoms, such as an

exacerbation of COPD due to excessive air pollution. The clinicians asked who would be

entering the medications into the app. They said it would be best for a nurse or someone from the

patient’s health care team to enter the medications on a Dashboard to ensure accuracy and

reliability and to “ensure people are confident about the list” [C3]. “For adherence purposes, it’s

good to mention how often and when to take medications, as well as having the purpose of the

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medications.” [C3]. Clinicians also suggested having images of the tablets or medications appear

on the medication list to help patients recognize their tablets. Therefore, the display of the

medications list should be considered so that it is applicable to a variety of chronic

conditions.

Adjust the Content of Individual Medly Apps for Primary Care

Patients in primary care clinics have not necessarily obtained the same training that patients in

specialized clinics did. When patients with COPD in the primary care clinic were asked to go

through symptoms questions that were being used in the Medly COPD app, they were not aware

of the meaning of certain words: “What is a reliever?” The same patient answered, “Shortness of

breath, yes I would know,” but “sputum – that I don’t know. I would say no to all of those.” The

patient stated that COPD questions related to sputum volume, color and thickness do not apply to

him. However, once the study coordinators explained to him what is sputum (the patient was

English speaking), he realized what it is, he stated he does notice changes in his sputum,

“Sometimes when I cough. It’s usually clear. If it’s yellowish, it could be infection. First thing

in the morning, I clear my throat, so sputum. It seems to be normal, doesn’t change much. If I

get a cold, then the color changes” [P15]. The patient said he would then use his reliever when he

has a cold. Another patient was surprised he would have to answer his COPD symptoms daily,

“Sputum, am I expected to check my sputum daily?! This is asking for changes in color, amount

and thickness. To be honest, a lot of these questions wouldn’t enter my mind to check for.

Sputum color is not something I generally analyze. If I have a cold, then I would have a lot of

sputum. Sputum thickness – didn’t even know of it. Any unplanned healthcare visits? Would

that mean any? If I use my reliever, it would be multiple times a day” [P14]. The same patient

continued, “How does this app help manage COPD for me? Oh it can tell me about flare-ups…

Problem I have here with symptoms is do you want answers when everything is normal or when

something happens?” [P14] Therefore, when designing the content and features of the app,

it should be kept in mind that the patients in primary care clinic are more varied in their

knowledge, training and understanding of their health conditions. Additionally, the

frequency of monitoring required varies for the patients based on the severity of their conditions,

so that should be taken into consideration as well when designing the app.

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The focus of the second round of usability testing was to test the designs and features of the

MCC application for the management of diabetes and hypertension. Paper prototypes were used

for this round of usability testing in order to facilitate fast modifications and refinements so that

major usability issues could be addressed quickly, since the development of the MCC app was

underway with the help of two software developers. The designs went through several iterations

based on discussions with members of the design team and personal health information team at

the Centre for Global eHealth Innovation. Help from a designer from the Human Factors team

was received in transferring the concepts to the current graphics. The hypertension algorithm was

a new feature that was added into the app, along with a corresponding trend review alert that

would be triggered if a user had five days of consecutively high or low blood pressure readings.

Some sample designs used for the second round of usability testing were as follows:

(a) Main Page - contains list of items to complete and a button ‘Let’s Begin’ to start the guided wizard.

(b) Immediate Feedback – for the readings is available. Actions and alerts due to a certain reading will also be displayed immediately as a reading is transfferred to the phone.

(c) Latest reading taken today are displayed. Tapping on each tile will lead to all the past readings recorded for that parameter.

Figure 7: Screenshots from prototype of MCC app used in Usability Testing Round 2.

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Second round of usability testing was conducted with 7 clinicians and 5 patients over a 3-month

period. Compared to the patient sample in the first round of usability who were mostly 65 years

old, the patient population for this second round of testing was younger, all within the 40 – 64

year range, and more comfortable using technology. Three of the patients had smartphones,

which they were more comfortable using, and they all used their smartphones frequently. Two of

the patients had cellphones and they were comfortable with using their cellphones. All the

patients were computer owners and used it at a regular basis. Comparison of the patient sample

in the first and second round of usability testing demonstrated the transition in their abilities to

cope with technology. The younger group was a more avid technology user. Also, because the

group for the second round of usability testing was in the early stages of diabetes, none of them

had insulin-requiring diabetes. Instead required diabetes pills to manage their blood sugar levels.

All the patient participants wore glasses, and during the testing sessions a couple of them

commented that they had forgotten their glasses and thus may have trouble visualizing the screen

of the app.


Characteristics

N (n = 5)





Chronic Conditions for Study Eligibility Hypertension + Diabetes (Oral Meds) 5

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Table 12: Patient technology-related characteristics for Usability Testing Round 2.

Total (n=5)

N



Very comfortable 2 Comfortable 1 Somewhat comfortable - Not comfortable -

What type of smartphone do you use? Blackberry - iPhone 1 Android 2


Frequently (few times a day) 3 Sometimes (few times a week) - Rarely (few times a month) - Never -


Voice calls 3 Text messaging 3 Email 2 Information seeking 2 Scheduling 1 Information storage (e.g. contacts) 3 Other 1



Very comfortable - Comfortable 2 Somewhat comfortable - Not comfortable -


Frequently (few times a day) - Sometimes (few times a week) 2 Rarely (few times a month) - Never -








Distance 1 Reading 1 Reading and Distance 3

All 7 clinicians recruited for the second round of usability testing were from the primary care

clinics from Toronto Western Hospital or Mount Sinai Hospital. Testing was conducted with

family physicians for this round because the first round of usability testing had demonstrated that

the features and content of the app needed to be adapted in order to meet the needs of patients in

the primary care clinics if that is where the app is to be deployed in the future. Therefore, the

second round of usability testing was narrowed down to meetings with family doctors in order to

validate the contents of the app and determine the appropriateness of the app for a primary care

clinic. All usability testing sessions lasted about 30 – 45min.

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The prototype designs were based on the scenario that the measurements of blood pressure are

taken two days a week, Mondays and Fridays, during morning and evening; and blood glucose is

measured daily during breakfast and dinner time. Following were the main points that were

gained from this round of usability testing.

Add Reminders to Notify the User to Launch the App

During discussions regarding navigation through the MCC app, one of the screens designed was

a ‘welcome back’ screen. This screen was designed to accommodate a scenario where the user

returns to the app later in the day and has to take some more measurements, for example, their

evening blood pressure readings and dinnertime blood sugar readings. The app would state

‘welcome back, it’s time to take your next set of readings for today’ and display the readings that

the user still has to complete for today. Although this screen was to be incorporated into the app,

it made the back-end algorithm for programming more complicated. Therefore, in order to have

the app up and running in the given time, the welcome-back message was removed from

development. Nevertheless, it was presented to the users during usability testing sessions since

paper prototypes were being used. The screen received positive reviews from the users because it

assisted them in understanding that they were returning to the app for the second time today in

order to record the next set of required readings.

However, one of the clinicians made a good point that the user should first be reminded to launch

an app: “Will they be seeing the ‘welcome back, it’s time to take your next set of readings’ when

they launch the app? If this was popping up on someone’s screen, “It’s time to take your readings

for today” should be a reminder. If they have reminded themselves, then when they re-launch the

app for second set of readings, they should have another message, ‘Thank you for coming back’

on the screen” [C2U2].

For the next iteration of the app, the app should have a generic initial reminder to notify the

user to launch the app. The pop-up reminder could be a short message such as: ‘It’s time to

take some readings.’ This will prompt the user to launch the MCC app. When the MCC app is

launched, then the app should display a message such as ‘Welcome back Jane’ or ‘Thanks for

coming back Jane’ and ‘It’s time to complete your readings today’ and list the measurements the

user has to complete.

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Add a Sync Button

Clinicians familiar with health apps with Bluetooth connectivity inquired about the transfer of

readings from the external devices to the smartphone. One of the clinicians was familiar with the

Bluetooth connectivity issues and stated that there should be a sync button somewhere on the

screen: “What happens if it doesn’t work, it doesn’t sync. Maybe there should be a sync button

here too because guarantee it will not always sync properly” [C2U2]. Currently, the digital

blood pressure monitor used with the Medly apps is A&D model UA-767 Plus BT-Ci. The

transfer of blood pressure readings from the device to the smartphone is triggered only when a

new blood pressure reading is taken. Thus a sync button would not be useful for the blood

pressure monitor. However, the BluGlu (an adaptor that relays data from the glucometer to the

smartphone via Bluetooth connection) for the One Touch Mini glucometer could benefit from

the addition of a sync button. Currently, a blood glucose reading transfers to the phone

automatically when the BluGlu that is connected to the glucometer is paired with the phone. If

there are un-transferred readings on the glucometer, then those readings will transfer to the

phone when the user takes a new blood glucose reading. Manual syncing is required when there

are un-transferred readings on the glucometer and the user wants to transfer the readings without

having to prick themselves to make a new blood glucose measurement. In that case, the user can

tap on a sync button and those un-transferred readings transfer to the phone automatically.

Additionally, based on previous experiences of Medly Diabetes app that utilizes the BluGlu and

One Touch Mini, there are possibilities of syncing errors and the user can access troubleshooting

steps once they tap the sync button. Taking these scenarios into consideration, a sync button

should be added to the MedlyMCC app.

Add Labels for Before and After Meals

Several patients and clinicians inquired whether the MCC app differentiated between blood

glucose readings taken before and after a meal. While one of the users was on the blood glucose

readings page consisting of a list of readings taken in a tabular format, he stated, “It doesn’t tell

you whether it’s before or after breakfast.” [P3U2] This patient’s before meal range tends to be

around 7 mmol/L and after meal range tends to be 11 mmol/L. In the usability studies, most

patients measured their fasting blood glucose before breakfast. Some also monitored before

lunch, dinner and bedtime. Some monitored their readings after a meal, and some monitored both

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before and after a specific meal. One patient had mentioned, “When I started taking insulin, I

would measure my blood glucose morning before breakfast and then after breakfast. And two

hours after every meal, so a total of 4 to 7 readings. It seemed to be rather excessive. I did this

for 2 months and then saw it made no difference, so I reduced it to two times a day.” [P14] For

diabetes, monitoring blood sugar levels on a regular basis provides patients with immediate

feedback on whether what they are doing is working or not, and it serves as a motivation to keep

up actions that are working or make changes. One tech-savvy 60-year-old patient downloads his

blood glucose readings from his glucometer to his computer and creates graphical displays to

analyze how well he is doing. He stated, “One of the break out I have on my graph is before and

after meals. Before meals help me regulate my insulin more than the after meal counts. If I’m

running high for 4 meals, it drives me to increase my rapido insulin. If I see my pattern high in

the mornings, I know to increase my insulin. After meal, depends on what I ate, has more

variability to it…It helps me regulate myself, the insulin so it’s useful to see overtime.” [P4U3]

A few clinicians also mentioned that it would be useful for patients to be able to tag their

readings as before or after meals and observe the differences in patterns of highs and lows.

Therefore, for the future, the addition of before and after meal labels should be taken into

consideration. Currently, the trend algorithm for the MCC app was obtained from the Medly

Diabetes app where a trend alert is triggered when there are three consecutive days of high or

low readings for a specific mealtime: overnight, breakfast, lunch, dinner or bedtime. The

algorithm does not take into consideration the before and after meal readings individually

because it is based on meal times of the day. So changes in the trend triggering algorithm may

also need to occur if before and after meals labels are included into the app. Conversely, the

before and after meal labels can only be used for graphs, to show users patterns in their before

and after meal readings.

Rework the More Button in the Action Bar

The action bar in a mobile app is a feature that provides a dedicated space to display the name or

icon of the app and provides user actions and navigation modes [87]. One of the items on the

action bar in the MCC app was the “More” button to indicate action overflow. If the user were to

tap on the “More” button, then a list would populate with other features of the app that the user

could navigate to. During the usability testing, when the patients were on the Readings Page

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containing the square tiles for Blood Pressure and Blood Sugar, they were asked, “Where would

you click if you wanted to know more about your blood sugar readings?” The purpose of the

question was to observe whether the users would tap on the square tiles so that they could view

more information such as history of recorded readings, trends, etc. Instead multiple users tapped

on the “more” button at the top of the page in the action bar such as P4U2 and P5U2, one was an

avid iPhone user and the other was a basic cellphone user, indicating the actions of tech-savvy to

a not-so-tech-savvy user. The “More” button (Figure 7a) should be reworked in terms of

what items or features will be listed in this action overflow button.

Use Audience-Appropriate Terminologies

A question asked during the usability testing was whether potential users of the MCC App are

more familiar with the term ‘blood glucose’ or ‘blood sugar’. As one clinician stated, “I assume

they know that glucose and blood sugar are the same and they understand the right terminology”

[C1U2]. Most patients agreed to that they knew both terminologies. However, clinicians and

patients also concluded that they actually use the word ‘blood sugar’ on a day-to-day basis. One

clinician for example said, “I use the word sugar with my patients. It’s more commonly used.”

[C3U2] Therefore, to enhance the approachability and friendliness of the app, the word

‘glucose’ was replaced with ‘sugar’.

Under the assumption that the patient audience would not be familiar with the word ‘trends’, the

phrase ‘Start Trend Review’ from the Medly Diabetes app was changed to ‘Start Review’ for

when a trend alert was triggered. Few of the participants showed hesitance with the word “Start

Review” during the usability testing. One user stated “Start Review … I don’t know about Start

Review…Figure out what went wrong. Start Review sounds like you’re reviewing results. I

would change it ‘let’s check the possible causes’. Something shorter but something that refers to

that.” [P3U2] Therefore, the phrasing for the action button to prompt the user to start the

trend review should be rethought and possibly the original “Start Trend Review” is most

appropriate.

The word ‘Critical’ was another term that was reconsidered and changed. Clinicians had stated

early on that hearing the words ‘Critically Low’ or ‘Critically High’ would cause worry and

anxiety in patients. In order to minimize the anxiousness due to such a term, yet express the

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urgency of the situation, the phrase was changed to ‘extreme high’, ‘extreme low’ and then was

subsequently changed to ‘very high’ and ‘very low’ to create a more calming effect. Patients

understood the significance of the alert messages containing the term ‘very’ and the intensity of

the message was bolstered by the colors, icons and the reading values: “The red is good. It’s

telling me warning… and that arrow tells me watch out!” [P1U2]

Review the Blood Pressure Instructions Pages

Clinicians and patients alike appreciated the additional instructions page providing proper

techniques for taking blood pressure measurements (Figure 8). However, multiple clinicians

questioned the three check-marked items listed under ‘Before taking your blood pressure, make

sure that you have:’ since these items were not applicable to all user scenarios. The first item

“not taken your blood pressure medications” raised questions because many patients may have

already taken their medications first thing in the morning and thus this requirement to measure

blood pressure before taking any medications was not applicable. The second item “not eaten

anything for the past 2 hours” was also considered insensible, because clinicians questioned

whether it made sense clinically to wait 2 hours after eating to measure blood pressure.

Referring to the instructions page, a clinician summed it up as, “this is ideal but people will not

follow this. They won’t know about all of these conditions. Re-think this one maybe.” One

clinician said to add “Have not done physical activity for past 2 hours” because otherwise the

user’s blood pressure may still be high due to the exercise. The items listed in Figure 2 appear to

match the guidelines listed in Hypertension Action Tool Instructions for Health Care Providers

by Hypertension Canada. However, if the patient is measuring their blood pressure in the

evenings for example, the instructions telling the patient not to have taken any medications

seems inappropriate.

Secondly, three of the clinicians suggested that it may be better to provide the patients with this

checklist in a more visible manner before they start taking their blood pressure medications:

“Problem is that what if patients read the instructions afterwards, it doesn’t tell them not to take

the reading, but just the optimal way. Highlight during the training that they do the readings first

thing in the morning. If they forget the steps, it’s nice to have this.” [C2U2] Another clinician

said, “So if the patient has had caffeine or smoke a cigarette they will get a high reading. Maybe

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it would be better to present all these scenarios before telling them to take their readings. A list to

check off.” [C3U2] However, a potential problem would be: “patients may not take a reading at

all because they won’t meet the requirements. So if we do want them to take readings, then leave

it the way it is.” [C3U2] Taking different feedback into consideration, it may be better to keep

the additional instructions for blood pressure accessible if the patient taps on ‘more info’. A

simple basic instruction at first glance is more appropriate, because seeing an extensive checklist

on a daily basis would become repetitive. Nevertheless, the contents of the blood pressure

instructions page should be reviewed again and re-validated by a team of clinicians that

includes a hypertension specialist and family physicians.

Figure 8: Blood pressure instructions page.

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Question the Symptoms when Extreme Blood Pressure Readings

The hypertension algorithm being used for the second round of usability testing would be

triggered once the user completed a pair of individual blood pressure readings. When it would be

triggered, it would process the data and determine the patient’s overall today message, action

message and whether an alert needs to be sent. There were five categories for the readings:

critically low, low, normal, high, critically high. If the user had critically high or low readings on

Day 1, then the action message would state “Continue to monitor your blood pressure for next 2

days.” If the readings continued to be critically high or low on Day 2, then the action message

would state “Measure your blood pressure again tomorrow.” Finally, if the readings were still

critically high or low on Day 3, then the action message would be “Please call your doctor’s

office to book an appointment asap”, and an alert would be sent to the clinician after the user had

three days of consecutively critically high or low readings.

Most clinician identified the action message to be lacking one important part – asking the patient

about their symptoms. “If the person’s previous blood pressure reading was 110, and they don’t

feel any symptoms, then they may simply continue taking their blood pressure readings as

usual…if the last readings were 140/80, and now it’s 220. Something is wrong. There is false

info from your app when they clearly need to get some better advice… So if there are no

symptoms, then measure for next 2 days. If yes symptoms, then ask about symptoms. Ask [the

hypertension specialist] about what he thinks about medical advice” [C2U2]. One clinician

suggested to add the phrase “Seek medical care if you have severe symptoms.” He added that the

app “should go after symptoms. It’s never wrong for the person to call and get advice. If you are

unwell or worried about your blood pressure readings, consider contacting your healthcare

provider. It’s never wrong to contact your doctor” [C1U2]. Another clinician also said “If it’s

220 for example, then the patient should probably seek medical attention. Sometimes up to 220,

the patient may not feel any symptoms. They would probably feel symptoms of dizziness

headaches etc. at 240” [C2U2]. This clinician suggested to add the phrase “Call your doctor if

you’re feeling unwell” for the Day 1 and 2 action messages because there’s no need to send them

to emergency necessarily. Therefore for consecutive usability sessions, the action message for

Day 1 was changed to “Continue to monitor your blood pressure for the next 2 days. Call your

doctor if you’re feeling unwell.” For the Day 2, the message was adjusted to “Measure your

blood pressure again tomorrow. Call your doctor if you’re feeling unwell.” With this new

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addition, the clinicians provided positive reviews during the later usability tests, such as

“Ah, good you’ve talked about symptoms” [C6U2].

One patient during the interviews had mentioned that his blood pressure has “been over 200

before. Well, when I get the nosebleeds, I know it’s really high” [P9]. Taking cases such as this

as well as feedback about symptoms from the clinicians, there is more room for improvement in

the app. Once a critical alert is generated, the user should be prompted to complete a short

questionnaire asking them about their symptoms. This was suggested by a couple of the

clinicians because patients may be unaware of symptoms they should look out for: severe

headaches, shortness of breath, nosebleeds, etc. One clinician stated: “We need clarification

with [hypertension specialist] about this. If the person was quite elderly in their 90s, I would be

concerned about their readings even on a one day basis, depending on their symptoms. Maybe a

screen pops you to symptoms questions. Are you dizzy? Headache? Do you feel unwell? If they

answer yes to either of those questions, then please contact your healthcare provider or consider

going to your local emergency department or speak to someone. I think this may need more

discussion” [C1U2]. Therefore, if the user acknowledges that they are feeling some of the

symptoms of hypertensive crisis, then further instructions should be provided to the user to

seek emergency medical treatment. As well an alert should be sent to the clinician(s)

involved in the care of that patient informing them of the situation. Possible symptoms to

ask hypertensive patients are listed in Table 13.

Table 13: Symptoms questions for hypertensive patients [88].

Symptoms for Elevated Blood Pressure

• Headache • Dizziness • Blurred Vision • Nausea or Vomiting • Chest Pain or Shortness of Breath

Redesign the Feedback for Two Consecutive Blood Pressure Readings

Blood pressure was the only parameter that required users to take two consecutive

measurements. When the user took their first blood pressure reading, the user would receive

immediate feedback whether the reading is high, low or normal; and they would be told to take

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their second reading (Figure 9). Thereafter when the user took a second blood pressure reading,

the user would again receive feedback whether that second reading is high, low or normal; but in

addition they will also be given an action message based on whether a majority (75%) of the

readings today fell within a certain category (Figure 10). In the scenario shown in Figure 10, the

user had one normal reading and one high reading. Since the readings are stuck at a 50-50

situation i.e. the overall readings for that user are neither normal nor high, the patient is given the

action message ‘No action required’.

Figure 9: Feedback given after first blood pressure reading.

Figure 10: Overall action taking into account first and second readings.

This was found to be confusing for clinicians and patients alike: “This is a confusing message,

one is normal. One says high. It’s not clear to me or patient, that I’ve got a high reading, so it’s

okay? I realize you’re trying to keep text to minimum but it needs to be put into perspective as

in what this means. This one doesn’t provide interpretation, that’s confusion. You need a

message that says ‘Either one of your readings is high. No action required today, continue to

monitor’” [C1U2]. Therefore, the blood pressure feedback page was redesigned so that the

first reading would not be categorized, as shown in Figure 11. The feedback and overall

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action message would be given only after the patient had also completed a second blood pressure

reading, as shown in Figure 12.

Figure 11: Updated version of first blood pressure

reading page.

Figure 12: Updated version of blood pressure

feedback page.

Another point was made about these screens regarding the message instructing patients to take a

second reading. Initially the message was ‘You can take your 2nd reading as soon as you’re

ready’ as shown in Figure 9. But it was mentioned by a clinician that it would better to instruct

the patient to wait one minute (which is also written in the detailed blood pressure instructions

page in Figure 8 as per Hypertension Canada Guidelines) before taking their second reading as

that is an optimal time interval to get more accurate readings. So the message in later usability

tests was changed to ‘Now wait 1 minute, then take second your second reading’ as shown in

Figure 11, to provide users with more definite instructions. However, a physician specialized in

hypertension commented that patients would not likely wait one minute, especially on a daily

basis. They might find the wait to be cumbersome. Therefore the message was altered to simply

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‘Please take your 2nd reading’ in later prototypes. Considering the different suggestions by

different clinicians, it is necessary to validate the exact phrases of the instructions once

again.

Update Action Message for Blood Sugar Readings

The MCC app generated an action message stating, “You know what steps to take” when a very

high or very low blood sugar reading was captured (Figure 13). However, this message was

found to be vague by several patients and clinicians during the usability testing. “I don’t think

they know what steps to take and it’s not clear what steps to take. It’s much harder to bring down

your sugar level,” [C1U2] stated one clinician when he saw the instructions for a very high blood

sugar reading. Another clinician shared the same sentiments, “This is not enough. This person

might as well be semi-comatose. So this needs to have more action. They need to take something

immediately. You know what steps to take may or may not be true. I think they should take

something to raise their sugar, such as orange juice. Check with the your diabetic expert”

[C2U2]. The diabetic expert from the diabetes clinic was consulted regarding the action

messages. He stated that his patients were well trained and would know what actions to take if

their blood sugar levels were extremely high or low and thus the message ‘you know what steps

to take’ inherited from Medly Diabetes app would suffice. However, in subsequent meetings, the

phrase was updated to ‘Take steps to raise your blood sugar’ for critically low readings (Figure

14) and ‘Take steps to lower your blood sugar’ for critically high readings. For future

iterations, describing some steps such as drink a glass of juice, eat 3 or 4 pieces of hard

candy or glucose tablets, etc. could be added as suggestions to make the app suitable for a

primary care clinic where patients may not be getting the expert training that patients in

specialized diabetes clinics would. The content should be explored further and validated by

clinicians.

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Figure 13: Older version of blood glucose page.

Figure 14: Updated version of blood glucose page.

Break Down the Categorization of Readings

Medly Diabetes trend review algorithm and CKD blood pressure algorithm were used as a basis

for the development of the hypertension algorithm. The trend review portion of the hypertension

algorithm was largely based on the trend review of the diabetes app. Thus when developing the

categorization of blood pressure readings for the hypertension algorithm, five categories were

used: critically high, high, normal, low and critically low, in order to keep it consistent with the

five buckets of blood glucose. However, during usability sessions, a few clinicians suggested

that it may be better to add another category as well called ‘mildly high’ or ‘mildly low’. For a

blood pressure reading of 108/52mmHg for first reading and 105/66mmHg for second reading,

the app would give state ‘Overall today: Low’. However, one of the clinicians stated, “If we

were to categorize this medically, it’s a bit low. If you just stay to a person it’s low then the

person can also see it falls below their normal range. They may get worried about 52. They will

wonder, ‘is my blood pressure dangerously low?!’ So it needs to give a bit of perspective. This is

mildly low. Continue to monitor your blood pressure until you hit the critical ranges. You could

put this under the action under the target range sentence. It’s reassuring to the person. We could

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put ‘Overall today: Mildly Low.’ Coloring is nice” [C1U2]. For high blood pressure readings,

the clinician shared similar thoughts, “I think again what this doesn’t convey is this critically

high or just a little bit high? It says to continue to monitor. Have another line below “this is

mildly high, but not dangerous” this isn’t fully informative about the implication of this reading”

[C1U2].

Similar thoughts were conveyed regarding the blood sugar categories. The ranges for the blood

sugar categories shown in Table 14 demonstrate that during Usability Testing Round 2 the range

for high was quite large. Clinicians suggested that it may be better to break down the blood sugar

categories even further in order to display different action messages, particularly for the high

blood sugar category. The diabetes expert had also suggested that breaking down the high

category into two components, high and mildly high. However, since the diabetes trend

algorithm was developed using five categories, it would have been difficult to develop a new

algorithm based on seven categories: critically low, non-critical low, mildly low, normal, mildly

high, non-critical high and critically high.

As a short-term fix, the blood sugar ranges were adjusted to reduce the large range 7.1 – 25.0

mmol/L for the high category to 10.1 – 14.9 mmol/L, as shown in Table 14. This change was

made after consultations and validation by a diabetes physician.

Table 14: Different ranges for blood sugar during usability testing.

Very Low Low Normal High Very High Usability Testing Round 2

<=2.8 2.9 to 3.9 4.0 to 7.0 7.1 to 25.0 >=25

Usability Testing Round 3

<=3.5 3.6 to 3.9 4.0 to 10.0 10.1 to 14.9 >=15

As for the short-term fix for the hypertension algorithm, the development of the hypertension

algorithm based on the 75% rule was put on hold because further validation was needed. Based

on consultations with a hypertension specialist, the CKD blood pressure algorithm was

substituted into the MCC app. This CKD-MCC blood pressure algorithm contained seven levels

of categorization. For future iterations of the MCC app, the number of divisions of the

readings for different parameters should be made consistent because consistency acts as a

guide [86]. Feedback from the app should be consistent otherwise the user may notice that there

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are different categories for blood sugar, different categories for blood pressure and trying to

remember the differences in the meaning of feedback from the app will be cognitively

demanding. Furthermore, the algorithms for the different health conditions may need to be

adjusted to enhance consistency between different parameters. For example, the trend

algorithm for blood glucose is triggered at every 3rd high/low reading. In comparison the trend

alert for blood pressure is triggered at every 5th day of high/low readings. Further consultations

with clinicians are required to determine whether the time intervals for triggered alerts can

be made consistent as well.



A functional MCC smartphone application was tested for this final round of testing. Users were

able to navigate through the app to a far greater extent than the previous usability tests. Patients

were asked to measure blood pressure and blood glucose readings using a commercially

available digital blood pressure monitor and glucometer. The measurements were transferred

from these external devices to the Samsung Galaxy Core smartphone via Bluetooth connectivity.

A blood pressure simulator with preset readings and sample glucose solutions were utilized for

the different scenarios.


Third round of usability testing was conducted with 5 patients. The patients were recruited from

a diabetes clinic over a 2-month period, and they all had diagnoses of hypertension and insulin-

requiring diabetes (Table 15). Each usability session lasted around 30 – 45 minutes. None of the

patients had been part of this study previously.

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Characteristics

N (n = 5)






Hypertension + Diabetes (insulin) 5

All the patients in this round owned a smartphone (Table 16). They were comfortable using the

smartphones and used their smartphones either few times a week or few times a day. This group

of patient as a whole was more tech-savvy than the groups in earlier rounds of usability testing,

and this may have contributed to their opinions on the ease of navigating through the smartphone

app.

Table 16: Patients’ technology-related characteristics for Usability Testing Round 3.

Total (n=5)

N




What type of smartphone do you use? Blackberry - iPhone 1 Android 4




Voice calls 5 Text messaging 4 Email 2 Information seeking 2 Scheduling 2 Information storage (e.g. contacts) 4 Other -



Very comfortable - Comfortable - Somewhat comfortable - Not comfortable -


Frequently (few times a day) - Sometimes (few times a week) -

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Rarely (few times a month) - Never -


Voice calls - Text messaging - Web browsing - Other -






Distance 1 Reading 2

Both Reading and Distance 2


The 5 participants in the third round of usability round completed a post-study questionnaire

pertaining to their perceptions of the usability of the application and specific issues or areas of

the MCC application on the smartphone. Most of the patients found the MCC application easy to

use and easy to access on the smartphone (Samsung Galaxy Core) as shown by the scores in

Table 17. The guided wizard carried the patients through the actions they needed to take (e.g.

measure blood glucose and measure blood pressure) and thus they found it easy navigate through

the MCC app. Most of the difficulties were encountered with adding new information (i.e. blood

sugar readings). The users also had some difficulties with editing and correcting entries such as

changing their responses for the causes and fixes of repeatedly high readings (i.e. going back into

the app and adding high salt intake as a factor for repeatedly high blood pressure trend). That

was largely due to confusion with meaning of icons, as indicated by the low score of 2.6 (Table

18). Some of the users required their glasses to visualize the content on the smartphone app

however their response to the size of the characters on the screen was largely positive (Table 18).

Some of the language/wording (average score = 3.6) and amount of information on the screen

(average score = 3.4) received low evaluations (Table 18). This was mainly due to lack of

enough instructions for the patients to perform specific tasks. For example, the users stated that

the wordings on the blood glucose instructions page was not explicit in telling them to pull out

the glucose strip from the glucometer so that the data from the glucometer would transfer to the

smartphone. The findings and improvements required are explained in more detail further in this

section.

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Table 17: User responses to usability questions in the post-study questionnaire for Usability Testing Round 3.

Usability Questions

Very Difficult

1

2

3

4

Very Easy

5

Average Score (SD)

Overall, how easy was it to use the application? - - 1 1 3 4.4 (0.89)

How easy was it to access the application? - - 1 2 2

4.2 (0.83)

How easy was it to navigate through the application? - - 1 3 1

4.0 (0.71)

How easy was it to search for and review information? - 1 - 4 -

3.6 (0.89)

How easy was it to add new information? 1 1 2 - 1

2.8 (1.48)

How easy was it to edit entries? - 1 1 - 3 4.0 (1.41)

How easy was it to correct mistakes? - 1 - - 4 4.4 (1.34)

Table 18: User responses about the visuals from the post-study questionnaire for Usability Testing Round 3

Very Unsatisfied

1

2

3

4

Very Satisfied

5

Average Score (SD)

Application readability - - 3 2 4.4 (0.55)

Size of characters on screen - - 2 1 2 4.0 (1.00)

Language/wording 1 - 3 1 3.6 (1.52)

Amount of information on screen 1 - 1 2 1

3.4 (1.52)

Visual look/layout - - 1 2 2 4.2 (0.84)

Sequence of screens - - - 3 2 4.4 (0.54)

Application speed - 1 - - 4 4.4 (1.34)

Size of buttons - - 2 1 2 4.0 (1.00)

Shape of buttons - - 2 1 2 4.0 (1.00)

Meaning of icons 1 1 2 1 2.6 (1.14)

Size of icons - 3 2 3.8 (1.10)

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Reconsider the Flow of the Guided Wizard – Make it More Flexible.

Although the users found it easy to navigate through the MCC app due to the guided wizard that

carried them through the structured steps of first taking blood glucose measurements and then

taking two sets of blood pressure measurements, many patients expressed that desire to have

flexibility in choosing which measurement to measure first. It was observed during usability

testing that on the main screen patients would read the message “Hi Ramakrishnan! It’s time to

take your readings for today:” and then tap the area near the blood glucose and blood pressure

icons or on the words themselves, instead of tapping on ‘Let’s Begin’. This was observed with

almost all patients, because patients expected to be able to select the parameter they wanted to

measure first, that typically being blood glucose since it was a measurement they did most

frequently.

Figure 15: Main page of the guided wizard on the

MCC app.

Figure 16: Instructions page that allows user to temporarily skip taking a measurement.

This was an interesting issue to land upon. During the early stages of design iterations, there

were two different mindsets trying to converge on one point. One opinion was that patients

wanted flexibility, the choice to perform measurements in the order they would like. So that

approach lead to the checklist styled main page, as shown in the wireframes (Appendix A). The

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user would be able to take any measurement they wanted and that measurement would be

displayed on the main page, along with any alerts. Additionally, the user would clearly be able to

comprehend which measurements were completed and which were still required. This checklist

format list was also redesigned into a grid format, as shown Appendix A.

The opposite approach was to have a wizard guiding the patients step-by-step through the

measurements they need to take. This idea was obtained from the Blackberry Pearl version of

Medly HF that was used for the study [12]. However, the audience for that app was HF patients

from the HF Clinic, meaning they were required to take the same measurements at the same time

i.e. morning, everyday. The patients in the primary care clinic had much more varying schedules

and options in which measurements they need to take in the morning and other times of the day.

So the option to “Skip” or “I’ll do it later” was added to provide patients with flexibility to skip a

certain measurement and come back to it when they can (Figure 16).

When resources were available for development of the MCC app in April 2015, development

started using the 4x4 square grid design (Figure 18), based on the checklist concept. Based on a

Product Review Meeting with members of PHIT on May 8, 2015, it was decided that instead of

the checklist method, development should focus on the guided wizard approach. Thus the main

screen of the app is shown in Figure 15, where the user should tap on ‘Let’s Begin’ to start the

guided wizard.

However, noting that patients would prefer to start the wizard based on the parameter of their

choice, the app design needs to accommodate for patients who want to be given the option

to choose which parameter they want to measure first.

Add a Snooze Button for Skipped Readings

Scenario 2 for Usability Testing Round #3 required users to skip the step requiring them to

measure blood sugar. The users were able to perform this action without difficulties by tapping

on the “I’ll do it later” button at the bottom of the instructions card. The users moved on forward

to record their blood pressure values. When they tapped ‘next’ the instructions card for blood

glucose would reappear, and even when they tapped ‘I’ll do it later’, this same card would

shuffle and reappear repeatedly. The users found this to be confusing and nonfunctional. They

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were unable to figure out how to navigate away from the instructions card and were exasperated.

One user rated the app to be 3/5 in terms of how easy it was to use. One reason for the unease

was this recurring screen: “Tapping, thinking that this screen should do something. I’ll do it later.

Sure. I’ll do it later again. It keeps going through it. I can’t go in and change the time. I don’t

know.” [P2U3] Another patient suggested, ‘Give the option of dismissing it for a period. Have

you used outlook? I would give the option to snooze. It will get repetitive very quickly.’ [P4U3]

Taking the feedback from the users, the idea of adding a snooze button for skipped

readings should be taken into consideration for future iterations. Currently, if the patient

skips a reading and closes the app, and later returns back to the app, then the app would display a

Welcome Back screen and lists the readings that remain to be completed. Conversely a screen

such as the one shown in Figure 4 can be utilized to lead the user back to the instructions

page for the unfinished readings.

Figure 17: Screen to guide users to complete unfinished tasks.

Improve Visibility of the Tab Bar

The tab bar in the most recent developed designs of the MCC app was not visible to the users.

“It’s very easy to use, but a few changes maybe. Color, so that I would see them. I am not

looking at the tabs, I’m looking at the word Medly and the [overflow button] but there’s not

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something written in a different text or whatever it is… It’s not guiding me,” said one user

[P3U3]. Improvement in color contrast and text sizes is needed because users did not notice the

two tabs for “To-Do” and “Readings” despite the phone being on full brightness. It should be

kept in mind that the older patients have poorer visibility especially without glasses.

Add Blood Glucose Instructions Page

Instructions need to be improved for taking blood sugar readings. Blood glucose readings

transfer from the One Touch Mini glucometer to the phone automatically, however the Bluetooth

transfer is triggered only when the test strip is pulled out of the glucometer. That’s when the

BluGlu goes into PC mode and then it takes a few seconds for the transfer of readings to occur.

During the usability testing, patients were forgetting to pull the test strip to trigger the transfer of

blood sugar reading from the glucometer into the phone. Four out of five patients had a tough

time remembering to pull out the test strip. In one scenario, after waiting for a minute, when the

coordinator helped the user pull out the strip, the blood glucose reading did not transfer over to

the phone. That is because if the test strip is not pulled out within a 10 seconds of the taking the

blood glucose reading, then it will take full 2 minutes for the reading to transfer over

automatically. Therefore, the instructions page of the MCC app should be improved. One more

point should be added to the blood glucose instructions page: “Pull the test strip out of the

glucometer” and then “Then the reading will transfer to your phone automatically”. This would

also provide guidance to users who were tapping on the blood drop icon during Usability Test

Round #2 and inquiring “How will we take the blood drop”? [P5U2]

Additionally, detailed instructions for the blood glucose readings needs to be created that

will be displayed when the user taps on “More Help” in Figure 16 above. Experiences with the

use of BluGlu and One Touch Mini have indicated that problems can occur with connecting,

pairing and syncing with the phone. The detailed instructions page for blood glucose should

provide steps patients need to take in case of trouble shooting, need of manual syncing and

transferring of older readings from the glucometer.

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Guide Users to Tap on Square Tiles to View Past Readings

The Readings Page shown in Figure 18 contains square tiles for each parameter, which the user

would tap in order to view a log of the readings recorded as shown in Figure 19. However,

during usability testing, all of the users needed cues from the study coordinator to let them know

that the square tiles could be tapped on. This issue was inherent from the previous usability

testing where users also did not realize that the tiles would navigate to a page with more

information. It was assumed in round two of usability testing that users were not tapping on the

tiles because they were viewing paper prototypes. However, even in the third round of testing,

patients were not tapping on the tiles. This indicated that better directives are needed for those

who may not be familiar with the tile convention. “I am used to tapping the screen, I was going

to the usual places of here and upper corners” [P4U3] said one the users. The users said it would

help if there was “something written” telling them they can view more readings. So a phrase

such as “Tap on the squares to view past readings” should be stated on the screen.

Figure 18: Readings page on MCC app.

Figure 19: Blood glucose log page.

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Fix Colors on Readings Log Page

Users provided positive reviews about the Blood Glucose (Figure 19) and Blood Glucose (Figure

20) Log pages. “It’s well laid out, clean, easy to understand,” commented one of the users who

had been involved in evaluating mobile apps. Users found the history of readings to be useful

and liked the tabular format. However, the colors for the contexts need to be reconsidered.

Couple of the users suggested changing the colors of the circles based on severity. “I don’t think

the colors may be necessary. I don’t think morning needs a color,” was a comment made by one

user who stated that it did not add any value to use different colors for morning, afternoon and

evening blood pressure readings. [P4U3] This was also echoed by P4U3, who said “red means

warning.” He suggested that the “color of the readings should be based on high, low, instead of

morning, evening and such. Green is good. Yellow is dangerous…red means warning.” Patients

in the earlier Usability Round #2 also had similar remarks. The colors were also causing

confusion in interpreting the trend icon. “I see trending. The color of the arrow is darker. Does

that mean it’s a more severe trend?” asked one patient because the squiggly arrow for trends was

dark blue because the blood pressure readings taken in the evening were part of the trend.

Therefore the colors of the Readings Log Page need to be revaluated and be made

purposeful.

P2U3 also mentioned that he was unable to see the grayed out “Afternoon” and “Evening” text

as shown in Figure 20. When there are no readings taken for a certain day or context, the text is

grayed out. Whereas when there are readings recorded, the text is black. The patient said maybe

if he had brought his glasses, he would be able to see the gray text. This comment is similar to

one echoed by a patient in Round #1 of usability testing. She had also commented that she was

unable to see gray or light blue text properly, and the best contrast for her age is black text

against white background. Therefore, the colors of the text on the Readings Log Page need to

be adjusted to accommodate for the older audience that the MCC app is geared towards.

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Figure 20: Blood pressure log page.

Figure 21: Trend information page.

Provide a Compiled List of Alerts

Users commented that the app was “very easy to use” when considering the To-Do guided

wizard. However, all users struggled to navigate to the trend review section of the app whether to

view it or to make edits to their causes and fixes. One user commented, “Checking something off

doesn’t bring attention to that. It brings attention to me, but it doesn’t bring attention to when I

wanna remember it for the doctor. I have to scroll back through everything” [P3U3]. Another

patient in the earlier usability round #1 had said he liked seeing important events on the timeline

and was trying to tap on specific events to obtain more information on it. Therefore, the app

should consider a page such as Timeline where all alerts are assembled reverse

chronologically, enabling end users to access all alerts including trend reviews through one

central point. This Timeline will be similar to Medly COPD’s Storyline and would be one of the

main features listed in the Menu. Having all alerts compiled in this manner would reduce the

amount of layers the user has to navigate through to demonstrate their alert history to their family

doctor or other care providers.

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Rethink the Trend Review and Edit Icons

The squiggly trend symbol shown in Figure 20 was understood by some users to indicate high

readings. However, it was not clearly serving its purpose to indicate that all readings with the

squiggly arrow were involved in the same trend. Scenario 5 of the Round #3 of usability testing

required patients to make edits to their causes and fixes by accessing the Trend Information page

(Figure 21) via the Blood Pressure Log Page. It was not obvious to all users that they could tap

on the arrow to navigate to another page. Older patients tend to be more hesitant in tapping

around the app. “I would go to where the high blood pressure is, edit my trends… but the arrow.

That is very bad,” commented one user [P3U3]. Another user also commented on the trend

arrows, “I don’t have my glasses. I did notice them but they weren’t apparent to me what it

was…That did not resonate with me. It’s not clear, it doesn’t tell me I can edit there. It tells me I

can see a trend” [P4U3]. Patients in Usability Round #2 had also needed guidance from the study

coordinator to help them navigate to the Trend Information Page to make edits. Therefore the

symbols and colors of the trend need to be reevaluated and maybe the symbols need to be

reinforced by words.

Acknowledge Successful Completion of Trend Review

After answering the causes and fixes, one user mentioned she would like some sort of ‘good job’

or ‘great! You’ve identified some reasons for your high trend. Please contact your health care

provider if you have any questions.’ She elaborated, “I like this part, but getting some sort of

feedback ‘good job or make a note of what you would do differently’ would be nice. Therefore,

in future iterations, the user should receive a message acknowledging the effort the user

put in identifying the causes and fixes.

Ensure Measured and Displayed Readings are Consistent

During couple of the usability sessions, there was inconsistency between the latest reading

captured on the glucometer and the reading being displayed on the app. “Why is the reading

different?” said the patient unpleased. The reading on the glucometer was 4.2mmol/L whereas

the screen on the mobile phone showed “13.2 mmol/L”. The reading stored in the glucometer

from earlier in that day was being displayed instead of the latest reading that the user measured.

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It is necessary for the reading on device should match the reading that is seen on the phone

because it validates to the user that their devices are functioning with each other. More

importantly, action messages based on older readings will be providing users with the wrong

feedback and will not provide an accurate picture of their health status, thereby jeopardizing their

health. This bug causing inconsistent displays of blood glucose readings between glucometer

and MCC app was noted so that it could be fixed.

Restore Ability to Add Notes in Trend Review

Users indicated that it would be useful for them to be able to make notes reminding them why

they had a high or low trend. Visualizing the trend raises awareness and a feature to allow users

to add notes to describe the context would help them understand what they may have done to

result in the higher or lower readings. One of the options in the trend causes and fixes list is

‘Other’. In the Medly Diabetes app, users are able to type in their own notes into the app.

However, this capability was removed from the MCC app due to a bug that was complicating the

transitioning of the screen upwards when the keyboard would appear for text entry. When one

user was completing the trend review for a high blood sugar trend, he selected ‘Adjust Meals’ as

a fix and then asked, “It doesn’t tell you what? Like one extra egg. Some people write that

down…I think it should be more specific” [P2U3]. He commented that people should have the

ability to write down specifics. Whereas some patients write notes for themselves, others write

notes so they can show the information to their doctors. P3U3 for example said he would want to

write down more details about why he had a high salt intake, “Track salt intake, it doesn’t tell me

enough. When I go to the doctor’s office, and he says can you explain this? C’mon give me a

reason here. I won’t remember what was the reason.” Similarly, P4U3 understood the reason

why the trend view alert was triggered and while going through the causes and fixes list, he

added “I would give the opportunity to put some notes in. Sometimes I travel a lot for work. If

I’m travelling and there’s a trend I got over the 5 days because I’m travelling, I often don’t

remember it while I’m at the doctors. So I could say I was in Paris for this date and that’s one of

the reasons. Or my blood sugars have been a little erratic over 3 week period about 6 weeks ago

because I had case of sciatic so I was inactive and had diet changes. So I want to be able to make

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notes of that.” [P4U3]. Therefore, the ability to add short notes during completion of Trend

Review should be restored into the MCC app.

Display Target Ranges Graphically

During the first round of usability testing, it was recommended that the target range should be

displayed to the user to provide them with context of how their latest captured measurement

compares to their target goal. A family physician during second round of usability testing had

mentioned that ‘patients tend to see blood pressure readings as top versus bottom number. It

would be better to display diastolic and systolic ranges in two separate sentences. Your target

systolic range is: x to y. Your target diastolic range is x to y.” During the third round of usability,

it was suggested by a patient with knowledge of developing apps to “add graphics to visualize

target range and where does the user’s reading fall” [P3U3]. In multiple usability sessions,

patients would read the target range, and then start trying to interpret their measured numbers as

high or low. It was definitely more complicated to interpret the status of their readings for the

blood pressure readings because the text on the screen states ‘Your target range is 110/70 to

130/90.’ Trying to interpret how high or how low their reading is cognitively demanding. One

patient stated “ranges for systolic and diastolic could be shown in a better way to make

interpretation easier” [P1U2]. Therefore the visuals of the app should ensure interpretation

of measurements in comparison to target range is simple and easy to understand. Designs

created in May 2015 (Figure 23) were created based on the idea of a sliding scale where the

diagram would convey the context of a number in relation to its benchmark. However, having a

sliding scale diagram added complexity to the programming of the app, and thus visuals were

adjusted to accommodate for the limited time available for development of a functioning app.

However, for future iterations, it would be useful for the patient audience to have a visual

representation of how their latest reading compares to the target range identified by their doctor.

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Figure 22: Current display of measured reading in MCC app with respect target range.

Figure 23: May 2015 design aimed to use sliding marker to provide context for measured reading.

Add Transferring Screen

Usability Testing Round #3 was useful because a fully functional prototype was able to be tested

allowing users to explore the app and navigate in any manner they wished. Referring to the

transfer of the blood glucose reading form the glucometer to the phone, one of the patients

laughed and said “I wonder how long it takes” [P3U3]. Patients were waiting for while and

needed some sort of validation that the phone was working in sync with the external devices, just

requiring some time to transfer. The transferring speed is inherent to the Bluetooth connection

capabilities and may not be able to complete the transfer much faster. Users were unclear what is

happening and whether something is happening in the phone once the reading is taken or not. In

order to ease the waiting process and indicate to the users that there is transferring of the

readings occurring, the app should have a transfer screen with a spinning syncing icon to

show that the transfer is in process.

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Discussion 5In accordance with the first objective of this project, this project provided insight into features

that would be beneficial for patients and clinicians in management of MCC based on the needs

identified through qualitative analysis. It also provided insight into design principles, as per the

second objective of this project, for designing an integrated health management system, which

guided the designs of the prototypes created over the course of this study. For example, one of

the design principles stated that the system should be intuitive and should provide guidance to

the users. This principle took into consideration factors such as a) many of the users of the

smartphone application would be older, b) older individuals in general may be less comfortable

with new technologies compared to the upcoming young individuals and c) with age, there are

changes in cognition meaning that individuals may be unable to comprehend or remember

complex menu structures of a smartphone application [77]. Therefore, as per this design

principle, the user interface should be easy as possible, the menu layouts should be simple,

complex features should be preprogrammed so older patients need to press one single button to

complete an action, and explicit indications are given from the system that the user has

completed tasks correctly. Another design principle for example was that the system should be

modular. This was important for a system aiming to aid individuals with MCC because the needs

of this population vary based on the combination of conditions and the severity of conditions.

Thus having the ability to add or remove components to better customize the application to the

needs of the patient could lead to better adoption of the self-management tool. Information

gathered from interviews with patients and clinicians and lessons learned from the process of

designing prototypes and evaluating the designs through usability testing, the third objective of

this project, provided insight into feature improvements that should be addressed in future

iterations of the MCC smartphone application.

Several issues were identified during the study that could impact the potential efficacy of the

intervention that was being designed. These issues were mainly related to the variance in the

severity of health conditions, whereby those with milder forms of conditions were more

concerned with establishing healthy lifestyle habits as opposed to performing frequent

measurements of health parameters that may be more suitable for individuals with more severe

forms of health conditions. There was much difficulty in patient recruitment from the primary

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care clinics for the conditions targeted in this study, and this should be taken into consideration

for studies aiming to implement the smartphone based telemonitoring system in the clinics.

5.1 Difficulties in Patient Recruitment

There was much difficulty in recruiting patients with a combination of two or more of the target

conditions. At the start of this project, the aim was to develop an MCC app for HF, COPD and

CKD patients. However, due to difficulties recruiting patients in the primary clinics with a

combination of these three conditions, DM was added into the project because it was a more

commonly observed condition in primary care clinics. However, searching for patients with

combinations of CKD, COPD, HF, DM also lead to very low recruitment during the start of this

study. In particular, it was difficult to find patients with CKD in primary care. According to

Ontario Renal Network, there are 12,000 people in Ontario with CKD requiring pre-dialysis care

and an additional 10,500 with advanced CKD, requiring dialysis [89]. It is highly likely that the

CKD patients are scattered throughout Ontario and thus their numbers in the clinics participating

in this study were low. The couple of patients with CKD diagnoses found in the patient roster

were very elderly. They were either unable to provide informed consent due to cognitive decline

or were unable to stay for long appointments and therefore unable to meet with the study

coordinator. Regarding COPD, although it is a leading cause of hospital admissions in Canada,

only four percent of Canadians are diagnosed with this condition [46]. With regards to HF, an

estimated 500,000 Canadians are diagnosed with this condition [22]. Considering that these

patients are scattered throughout Canada could be a contributing factor to the low number of

COPD and HF patients that could be recruited from the clinics participating in this study.

Hypertension was added to the list of target conditions later in the study and the rate of patient

recruitment improved, leading to the first patient being recruited for the study with having

hypertension and diabetes. The initial thought was to recruit insulin-requiring DM patients

because this population needs to take frequent measurements of their blood glucose and hence

will have more use of an app that helps track their blood glucose levels. However, the criterion

for insulin-requiring diabetes was another limiting factor in patient recruitment. According to the

diabetes educator at one of the primary care clinics participating in patient recruitment, around

70% of the diabetes patients in their clinic did not require insulin. Therefore, for the third round

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of usability testing, patients were recruited from a Diabetes Clinic at UHN. The clinic functioned

only two days of the week, yet sufficient numbers of patients were found within three weeks of

active recruitment.

Physicians from the family health teams participating in this study corroborated that while there

were many patients with one of the five target chronic conditions, there were much fewer

persons with two or more of these conditions. Because they were a small population, their visit to

the clinic were infrequent relative to the large number of clinic visits that occurred each day.

Statistics also demonstrated that the conditions targeted in this study are prevalent or of high

impact [2] [3] [4], but the actual number of those with our target combination of conditions is

lower [14] [11]. The situation was similar to a pyramid, where a small population of patient with

MCCs required a large amount of healthcare resources. Taking into account patients come in

once a year, once in six months, or once in three months, the frequency of finding eligible

patients was lower than expected. Furthermore, patients were being recruited from the patient

roster of only a few clinicians at each the primary clinics participating in this study, not the entire

repository of the clinic. That may have also contributed to the difficulty in patient recruitment.

The combination of HTN and DM was the most commonly observed combination during the

recruitment for semi-structured interviews, and multiple studies have demonstrated this

combination to be one of the most prevalent [11] [15]. Combinations of arthritis and mood

disorders (mainly depression) with diabetes and hypertension have also been found to be

prevalent [11] [15]. Interventions for these could be considered as an addition to a MCC

management tool.

5.2 Module to Assist Behavior Change

Chronic disease management has been identified as a solution to the rising prevalence and

burden of chronic diseases [14] [77]. Modifiable behaviors and lifestyle factors such as tobacco

use, physical inactivity, unhealthy diet, harmful use of alcohol have been identified as important

contributors to development of chronic diseases [24] [90]. Unhealthy lifestyle habits have also

been associated with the likelihood of developing multiple chronic conditions [90]. Changing

health behaviors and biological factors could potentially reduce the number of people developing

chronic diseases. According to WHO [24], healthy eating, regular exercise and not smoking can

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avoid 90% of type 2 diabetes and 80% of coronary heart disease. As a further example, 90% of

lung cancer deaths and 30% of all cancer deaths could be prevented in a tobacco-free society

[24].

Figure 24: Chronic disease risk factors are common to many conditions [24].

Multiple patients in this study had expressed their desire to establish healthy lifestyle habits, but

found it difficult due to factors such as pain, physical limitations, financial barriers or even lack

of motivation. Thus there is a need to support prevention activities and healthy lifestyle

behaviors. Telemonitoring technologies could be utilized to support patients in their decision to

adopt healthy behaviors and then to build or maintain their motivation to meet their goals.

Interviews with patients had demonstrated variance in patients’ motivations to carry out various

self-management activities. Self-management activities are those that promote health i.e. healthy

living, exercising, as well as those that are needed to manage an illness (i.e. manage symptoms,

medications, adapting activities) [91]. Some patients expressed that an smartphone app that

required them to take measurements of blood pressure or blood glucose would not be as

beneficial to them because they do not want to take their measurements more often than needed

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i.e. measurements taken during clinic visits were sufficient. Another patient for example realized

that taking her medications was necessary for maintaining her health, however, the repetitive

task of doing so was tiresome and would lead to her skipping her medications some times. This

demonstrated that a prerequisite for seeking self-management strategies is that the patient must

perceive a need for self-management and this aspect aligns with the HBM for directing behavior

change [91]. They must feel the need to get their symptoms under control or mediate the threats

to their health or want to find a new way of life [91]. Many patients go through similar processes

while attempting to integrate chronic illness management into their lives. Once they learn about

their chronic illness(s), they seek effective self-management strategies and consider the costs and

benefits of the different self-management strategies before deciding on which self-management

practices to follow, based on which they feel best fits into their life situations [91]. One

overarching concept from the interviews with the patients was that self-management practices

must fit into the patients’ life situation. Patients tended to weigh the effectiveness of self-

management against the costs such as extra effort required and inconveniences. To continue with

self-management practices, the patients needed to experience some effect or believe the self-

management was effective. Many participants considered the effects of medication against the

risk or experience of side effects. For example, one patient with high cholesterol stopped using

his medications because he believed the medication was harming his body. The MCC app should

explore interventions designed to promote and facilitate behavior change in this population [77].

The mobile application can help patients modify their health behaviors that guide patients

through a process of behavior change that could lead to healthy lifestyle habits and appropriate

management of their illnesses. The 5As Behavior Change Model could potentially be utilized as

a behavior change model to follow since it is commonly used in primary health care to guide the

interactions between health professionals and patients to detect, assess and manage smoking,

nutrition, alcohol and physical activity risk factors [27]. Development of these features was out

of scope for the MCC app for this project, but can be considered for future apps geared towards

patients with MCC. Potential benefits of behavior tracking would include giving insights into

their own self-management patterns, increasing motivation and facilitating informed

communication with their healthcare providers [28][92].

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5.3 “One-size-does not fit all” level of severities

It was realized early on in this project that the MCC app needed to be modular enough so that it

could be configured according to the health conditions of each individual patient. Therefore the

architecture of the MCC app was designed so that components could be added or removed

according to the needs of the patient, to provide a tailored intervention. However, it was also

later realized during this study that the app needed to be modular based on the severity of

conditions, because the type of care and self-management activities needed by patients depended

on the severity of their conditions.

Although challenges of managing individuals with MCC had been acknowledged in earlier

studies [14][25], the complexity of designing a self-management intervention was understood in

this study after attempting to develop a tool that would be applicable to the range of MCC

patients. The main concern was the variance in severity in the patients’ conditions. Most of the

algorithms leveraged in the MCC app required daily monitoring because they were developed in

collaboration with tertiary clinics and thus daily monitoring was suitable for patients who were

most ill and frequently hospitalized [33]. However, interviews and usability testing with patients

highlighted that many did not think the MCC app would be useful for them because they do not

need to monitor their parameters at home. These patients believed that their visits with the doctor

every 3 or 6 months were sufficient enough to maintain their health. The question then was

whom should the telemonitoring mobile health applications be targeting to support. Should the

goal be to design an intervention that serves patients with a range of severity? Or should the goal

be to serve one group of patients, either those with mild conditions or those with advanced

conditions? The answer may be that it really depends on what the project wants to achieve,

because one size does not fit all.

According to some studies, in order for telemonitoring to be successful, it may be more

appropriate to target patients who are most ill and frequently hospitalized [33]. Another study

reported that patients with moderate severity of chronic illnesses living in a community with

some level of support have developed resilient self-management strategies, including methods to

manage setbacks such as illness exacerbations [93]. It has also been reported that patients who

have been diagnosed with their illness longer proved to have better self-management [93], and

this was also a general observation seen in the interviews and usability testing with patients in

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the MCC project. This was not necessarily always the case because a few patients were unable to

achieve self-management abilities they would have liked due to factors such as lack of

appropriate support, financial hardships (e.g. unable to afford alternative therapies) or

unstructured life situations [91]. Nevertheless, it was clear that patients with chronic conditions

tend to or need to make adjustments overtime to the presence of health problems, which involves

a change in thinking and behavior such as modifying social activities according to treatment

schedules and learning to live with physical limitations [94]. These adjustments eventually

become an integral part of their everyday life. Further investigation should be conducted to

solidify the exact needs of patients in primary care who have a range of severity and difference

in life situations and support needed.

Based on this MCC research study, telemonitoring of parameters such as blood pressure and

weight through a smartphone application would be beneficial for those who need moderate to

frequent monitoring. It was observed that diabetes was one disease that affected patients on a

daily basis and thus many diabetes patients measured blood glucose daily. Thus the MCC app

would be useful in helping them track their blood glucose levels on a moderate to frequent basis.

However, only one patient in the entire study measured weight and blood pressure daily or

frequently (80 years old, with HF). Therefore, in order for the MCC app to be utilized widely in

the primary care populations, it should be made applicable to patients who do not need daily

monitoring. One method is to make the frequency of monitoring required in the smartphone app

to be flexible, as detailed in Subtheme A1. For people with mild to moderate severity of

conditions who did not see the benefits perceived from carrying out of monitoring, this lack of

benefits could be addressed by adding components related to establishing or maintaining healthy

lifestyle behaviors, as detailed in Theme B, in order to be applicable to those patients who would

not be benefitting from an alerting system because their health conditions are in a more stable

condition compared to the relatively ill patients [95]. Focusing on self-efficacy and teaching self-

management skills such as goal-setting and other behavior-change strategies would be effective

for these patients to achieve sustainable healthy behavior change [3].

Designing a smartphone application for primary care clinics with a spectrum of severity in

patients’ health consideration requires careful consideration. One solution could be to gear the

self-management towards patient groups based on severity of their conditions – either aim to

help those with severe conditions or aim to help those in the mild to moderate range. It would

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enable the self-care modules to be more focused on a specific population. However, if the self-

management tool aims to target general problems that patients with multiple conditions

experience (such as establishing healthy lifestyle behaviors, pain and symptom management,

etc.) instead of specific combinations of common conditions, then it could still be possible to

have one mobile application that can be used among a wider set of primary care patients.

5.4 Disease-Specific or Reading-Specific Intervention

Multiple chronic conditions is a complex phenomenon [96]. The presence of several health

problems results in a variety of interactions, and the results of the chronic conditions can be seen

in various forms, psychological and physiological [94]. Multiple medications required for the

treatment of multiple chronic conditions cause other problems, adding to the complexity of the

situation, causing exacerbation of symptoms or physiological parameters. Furthermore, not all

diseases have the same significance in the overall experience with multiple chronic conditions

[94]. Diseases that involve pain tend to be more distressing for the patients compared to those

with unnoticeable symptoms [94]. Multiple clinicians in this study cited lack of established

guidelines for management of combinations of chronic conditions to be a barrier in providing

care for their MCC patients. This has been also been noted in many other studies [97][98] that

clinical guidelines and disease management programs have been predominantly focused on

single-diseases. It has been stated that guidelines need to be tailored to clusters of diseases, and

not only to acknowledge the biology of the clusters, but also to provide support for coping with

challenges MCC patients may experience in general and specific to those clusters [97].

According to other studies, designing interventions around specific conditions should be

avoided, in order to avoid defining patients solely by their disease [6]. Parekh et al. [6] stated that

disease-specific instructions may be less important than problem-solving skills, because

challenges inherent to a single chronic condition may be common across other conditions. Smith

et al. reviewed the effectiveness of multiple interventions, and concluded that interventions are

more effective if they either target specific combinations of common conditions or specific

problems of patients with MCC [9]. Taking into account the lack of fully developed evidence-

based guidelines for MCC and the fact that clinicians identified that targets for the parameters

need to be adjusted based on the changes in patients’ health status, it could be more efficient to

have a reading-specific intervention. However, certain advantages to having disease-specific care

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could be lost in a generic program. Disease-specific algorithms provide the opportunity to guide

patients on specific actions required for each of their diseases, such as specific instructions on

what to do for COPD exacerbations or specific instructions about diuretic medications for CHF

based on significant changes in weight over a short period of time. Whether a disease-specific

self-management program would be more advantageous over a reading-specific program needs

to be explored further and validated by clinicians in order to ensure proper clinical guidance is

provided to the patients with MCC [99].

5.5 Implementation of Telemonitoring System

There are many promising examples of how telemonitoring can successfully address the

conditions that occur most frequently among older populations [25] [100]. A promising sign and

a critical success factor among older populations is to have the information and data transfer via

mobile devices to become more personal and tailored to end users [100]. For older adults, the

most important factors are likely improved care and survival [14]. In contrast, healthy lifestyles

and other behavioral factors may be more important areas to focus on for young and middle aged

adults whose conditions have not developed into severe stages [14]. Smartphone applications

have the potential to be used for disease monitoring, health promotion and self-management

[100], and thus they could potentially be used in primary care as well as tertiary care clinics.

Multiple papers including reports by Health Council of Canada [20] describe the importance of

starting to provide self-management support to patients in the primary care clinics. In 2002,

several other health professional associations including the College of Family Physicians of

Canada and the Canadian Nursing Association reported that primary healthcare should be more

involved in self-management support, and one of the key themes in the 2011 report was to

advance self-management support of complex chronic disease with increased role of primary

care. According to multiple studies, successful management of chronic conditions must be rooted

in primary care because they are in a unique position to take into consideration the effects of

multiple chronic conditions, take into account the person’s individual circumstances and tailor

treatment recommendations to attainable health care goals [10][15][20]. Through one-to-one

interventions via home visits, telephone or individual coaching, primary health care nurses,

doctors, and other professionals such as social workers and pharmacists may be able to provide

greater self-management support to complex patients [20]. Primary care providers need tools to

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be able to deliver self-management support as part of their routine care and smartphone-based

telemonitoring systems are a potential tool that could be utilized for this purpose.

Considering the system and workflow that a smartphone app would fit into, it would be safer for

a clinician to be monitoring the patients through a platform similar to the Medly Dashboard

(web-based server) where a clinician such as a complex care nurse is able to view the alerts and

notification based on the data patients collect and contact the patient directly to provide overall

support and feedback. Having a nurse managing telemonitoring patients has been observed in

multiple RCTs [43][45][53]. One of the primary care clinicians interviewed in this study

described the workflow for alerting in the clinic as follows: “In our clinic, the main contact

person is the nurse who gets all the phone calls. She triages them. If it is a diet related issue, she

passes it to the dietician. If it is a medicine related issue along with diet, she passes it to the

pharmacist and the dietician. And whatever recommendations we come up with, we confer with

the doctor. The doctor will say yes or no” [C4]. Figuring out the workflow of the clinics is

important in order for the alerting system to work efficiently, and as stated in Subtheme E1,

having a nurse to triage the alerts generated through the mobile application will be replacing one

workflow with another. Aside from primary care, the smartphone based telemonitoring system

for MCC could also be utilized in tertiary clinics with the involvement of triage nurses. Having a

nurse to triage the alerts is central to the telemonitoring system. Specialist nurses in tertiary

clinics would be in the ideal position to work in partnership with primary care clinicians for

effective communication and management of patients with multiple conditions across the care

continuum [95].

Multiple clinicians in the interviews had cited time and cost to be barriers and causes of worry in

managing alerts and responding to patient-related emails. Telemonitoring can potentially

increase professional workloads and require changes in the organization of services. Successful

implementation of the system would first have to take into account how additional roles and

responsibilities should be aligned with existing workflows and data management practices.

Secondly, appropriate funding models and support needs to be implemented to allow for health

care providers to spend the time needed for MCC patients and to expand the range of services

provided to them as well as the means by which they are provided (i.e. telemonitoring).

113

A few clinicians in the interviews had stated their concerns with having to log into multiple data

management systems in order to care for groups of patients. The ideal situation would be to

integrate the telemonitoring data with the electronic health records or external databases that are

being utilized by the clinicians. Basically, the system should enable healthcare providers to have

a quick and secure availability to a central repository where data captured by patients and related

to the patients’ health conditions are held. A platform such as Medly Dashboard could be utilized

as a web user-interface and server that are used for information exchange between multiple

facets involved in a patient’s care regimen. It would securely transfer data between the MCC

application installed on a patient’s mobile phone, lab results and medication lists, and an internal

server which hosts alert algorithms for patient care. It would allow users such as health care

professionals to view the exchanged information, monitor a patient’s status and manage the

patient’s chronic conditions. Such a system would enable decision-support capabilities that can

assist patients in managing chronic conditions.

Lastly, much emphasis had been placed on the lack of communication between primary care and

tertiary care clinics. To meet their complex needs, patients with chronic conditions often receive

care from multiple clinicians, who may work independently from each other resulting in

fragmented and poorly coordinated care for the patients. Ideally an inter-clinician tool could be

created so that multiple clinicians involved in the patient’s care can have access to the patient

data so they can also monitor the conditions. Development of an integrated, healthcare system-

wide shared data management repository would not only enable seamless communication among

clinicians regarding patient information, but it would also be ideal in interconnecting data

between patients’ smartphones and clinicians.

5.6 Strengths and Limitations

One of the strengths of the qualitative data collected in this study was methods triangulation

[101] because the information was obtained from multiple sources (patients, primary care

physicians, nurses, pharmacists and specialists) and multiple methods (semi-structured

interviews and questionnaires). Another strength of the qualitative analysis was analyst

triangulation whereby a second reviewer also reviewed the data. Having two researchers

independently analyze the same qualitative data set and comparing their findings provided an

114

important check on selective perception and interpretative bias [101]. Having the findings in the

study based on comparison of data obtained from different methods added to the credibility and

trustworthiness of the results [102].

A limitation of the study was the external validity associated with qualitative studies. Data were

collected from a few participants selected to be part of the study using a purposive sampling

technique. Therefore, the findings may not be generalizable to other populations. Patients were

recruited from clinics that were well established and had allied healthcare incorporated into the

care system. The clinics and clinicians participating in this study were more engaged in

management of their patients and also in facilitating research studies, and hence it could be a bias

as to why most patients were satisfied in the information exchange with healthcare providers.

Patients felt their doctors already had the test results before the patient came in for the

appointment, and they felt they were in good hands. The pharmacists were available within the

vicinity of the primary care clinics and kept a check on the medications the patients were taking.

The pharmacists helped patients with MCCs in organizing their medications using blister packs

or pillboxes, and that could be a reason why patients in this study did not complain about their

medications as is usually reported in other published studies [21] [85] [97]. Similarly diabetes

educators, dieticians, and nurses were also part of the primary care clinics and were highly

involved in patient care, and that may explain why patients found their family doctors clinic to

be very helpful. This may not always be the case for many patients and their providers in other

settings. So findings in this study may not be transferable to those who live in rural areas or have

limited access to healthcare providers.

Another limitation to this study was the limited number of patients with HF, COPD and CKD

who participated in this research. More than half the patients during the semi-structured

interviews and first round of usability testing had diabetes and hypertension. By the second and

third round of usability testing, all patients had diabetes and hypertension. Therefore, this study

was unable to delve too much into how the other chronic conditions affected management of

multiple chronic conditions.

115

Conclusions and Future Work 6This study highlighted that there is much complexity involved in trying to develop a tool that

would be applicable to the wide range of patients seen in the primary care clinic with MCC, and

the concept of one-size-fits-all is challenging to achieve and needs further exploration. Designing

an application that caters to the needs of primary care population requires careful consideration

of what is trying to be achieved by providing a self-management tool.

The features and design principles identified in this study can be used in future projects that aim

to develop a smartphone-based telemonitoring system for the management of MCC. Currently,

only one other smartphone application, called MedDiary, exists for patient self-management of

multiple chronic conditions [78]. Comparison of the MedDiary app with the Medly MCC app

reinforced the importance of customization in the care plans, communication with the care team,

and centralizing all the collected data. The latest version of the MCC app contained algorithms

for DM and HTN. Future iterations of the MCC application should incorporate the HF, CKD,

and COPD algorithms that have already been developed and test whether the algorithms can

work in conjunction with each other.

A feasibility study should be conducted to evaluate the effectiveness of the MCC application.

The MCC application in this project was designed with primary care in mind. However, the use

of the MCC application can be extended to tertiary specialty clinics, as long as there is a point-

person or nurse to triage the alerts. The feasibility study would provide insight into the impact of

the telemonitoring system on patient and provider experience, workflows, and adherence to self-

care management.

Use of smartphone-based telemonitoring for self-management of chronic conditions is relatively

new and many concepts are being tested. There are still many questions that researchers and

policy makers need to address to integrate telemonitoring technology into the healthcare system.

For example, how should the telemonitoring program be funded? What is the best approach to

enhance the communication between patients and their healthcare providers (i.e. primary and/or

tertiary)? Public policy will play an important role in supporting the availability of services for

patients to manage MCC. This study highlighted that one barrier in providing care for MCC

patients is that they often receive care from multiple clinicians, who tend to work independently

and have limited communication with each other regarding the patient’s care. Policy makers

116

need to be involved to reduce fragmentation and improve coordination between health care

providers. This can be accomplished for example by developing a province-wide integrated

electronic patient record (EPR) system, and integrating smartphone-based telemonitoring system

to it. Data collected on the smartphone could be transferred to the EPR and made available to

the multiple clinicians involved in the patient’s care, thereby enabling multidisciplinary work

among clinics.

This study further highlighted the lack of guidelines for treating different combinations MCC.

Thus governments, healthcare providers and chronic disease organizations need to collaborate

further and integrate their work to fill gaps in services and establish evidence-based guidelines

for proper management of patients with multiple health conditions. There was a difference in the

level and type of telemonitoring care needed for patients with varying levels of severity of their

conditions. It is thus necessary to invest in research needed to deliver care according to the

varying needs of these patients. Lastly, telemonitoring may require clinician phone calls or other

forms of communication that are not currently billable, or can potentially increase clinician

workloads by requiring additional time to monitor the patients. Thus, successful implementation

of the telemonitoring system would need appropriate reimbursement methods and funding

models to enable care providers to monitor and support MCC patients at the level of care needed.

117

Bibliography

[1] G. Paré, M. Jaana, and C. Sicotte, “Systematic review of home telemonitoring for chronic

diseases: the evidence base,” J. Am. Med. Informatics Assoc., vol. 14, no. 3, pp. 269–277,

2007.

[2] K. M. Schneider, B. E. O’Donnell, and D. Dean, “Prevalence of multiple chronic

conditions in the United States’ Medicare population,” Health Qual. Life Outcomes, vol.

7, p. 82, 2009.

[3] Canadian Institute for Healthcare Information, “Seniors and the health care system: what

is the impact of multiple chronic conditions?,” World Health, pp. 1–23.

[4] A. Jadad, A. Cabrera, F. Martos, and R. Smith, When people live with multiple chronic

diseases: a collaborative approach to an emerging global challenge. Granada:

Andalucian School of Public Health, 2010.

[5] A. G. Logan, M. Jane Irvine, W. J. McIsaac, A. Tisler, P. G. Rossos, A. Easty, D. S. Feig,

and J. A. Cafazzo, “Effect of home blood pressure telemonitoring with self-care support

on uncontrolled systolic hypertension in diabetics,” Hypertension, vol. 60, no. 1, pp. 51–

57, 2012.

[6] A. K. Parekh, R. A. Goodman, C. Gordon, and H. K. Koh, “Managing multiple chronic

conditions: a strategic framework for improving health outcomes and quality of life.,”

Public Health Rep., vol. 126, no. 4, pp. 460–71, 2011.

[7] T. Paget, C. Jones, M. Davies, C. Evered, and C. Lewis, “Using home telehealth to

empower patients to monitor and manage long term conditions.,” Nurs. Times, vol. 106,

no. 45, pp. 17–19, 2010.

[8] G. Paré, K. Moqadem, G. Pineau, and C. St-Hilaire, “Clinical effects of home

telemonitoring in the context of diabetes, asthma, heart failure and hypertension: a

systematic review.,” Journal of medical Internet research, vol. 12, no. 2. p. e21, 2010.

118

[9] S. M. Smith, H. Soubhi, M. Fortin, C. Hudon, and T. O’Dowd, “Managing patients with

multimorbidity: systematic review of interventions in primary care and community

settings,” BMJ, vol. 345, no. 1, pp. e5205–e5205, 2012.

[10] L. Lee and G. Heckman, “Meeting the challenge of managing seniors with multiple

complex conditions: the central role of primary care,” CGS J. C., vol. 2, no. 2, pp. 23–27,

2012.

[11] J. Sinnige, J. Braspenning, F. Schellevis, I. Stirbu-Wagner, G. Westert, and J. Korevaar,

“The prevalence of disease clusters in older adults with multiple chronic diseases – a

systematic literature review,” PLoS One, vol. 8, no. 11, p. e79641, 2013.

[12] E. Seto, K. J. Leonard, J. A. Cafazzo, J. Barnsley, C. Masino, and H. J. Ross, “Perceptions

and experiences of heart failure patients and clinicians on the use of mobile phone-based

telemonitoring,” Journal of Medical Internet Research, vol. 14, no. 1. p. e25, 2012.

[13] J. Barlow, C. Wright, J. Sheasby, A. Turner, and J. Hainsworth, “Self-management

approaches for people with chronic conditions: a review,” Patient Educ. Couns., vol. 48,

no. 2, pp. 177–187, 2002.

[14] A. J. Koné Pefoyo, S. E. Bronskill, A. Gruneir, A. Calzavara, K. Thavorn, Y. Petrosyan,

C. J. Maxwell, Y. Bai, and W. P. Wodchis, “The increasing burden and complexity of

multimorbidity,” BMC Public Health, vol. 15, no. 1, p. 415, 2015.

[15] A.-M. Broemeling, D. E. Watson, and F. Prebtani, “Population patterns of chronic health

conditions, co-morbidity and healthcare use in Canada: implications for policy and

practice.,” Healthc. Q., vol. 11, no. 3, pp. 70–76, 2008.

[16] L. García-Olmos, C. H. Salvador, Á. Alberquilla, D. Lora, M. Carmona, P. García-

Sagredo, M. Pascual, A. Muñoz, J. L. Monteagudo, and F. García-López, “Comorbidity

patterns in patients with chronic diseases in general practice,” PLoS One, vol. 7, no. 2, p.

e32141, 2012.

119

[17] K. E. Thorpe and D. H. Howard, “The rise in spending among Medicare beneficiaries: the

role of chronic disease prevalence and changes in treatment intensity,” Health Aff., vol.

25, no. 5, pp. w378–w388, 2006.

[18] I. Martín-Lesende, E. Orruño, A. Bilbao, I. Vergara, M. C. Cairo, J. C. Bayón, E.

Reviriego, M. I. Romo, J. Larrañaga, J. Asua, R. Abad, and E. Recalde, “Impact of

telemonitoring home care patients with heart failure or chronic lung disease from primary

care on healthcare resource use (the TELBIL study randomised controlled trial),” BMC

Health Serv. Res., vol. 13, p. 118, 2013.

[19] N. M. Clark, M. H. Becker, N. K. Janz, K. Lorig, W. Rakowski, and L. Anderson, “Self-

management of chronic disease by older adults: a review and questions for research,” J.

Aging Heal., vol. 3, no. 1, pp. 3–27, 1991.

[20] Health Council of Canada, “Self-management support for Canadians with chronic health

conditions,” no. May, pp. 1–64, 2012.

[21] E. A. Bayliss, J. F. Steiner, D. H. Fernald, L. A. Crane, and D. S. Main, “Descriptions of

barriers to self-care by persons with comorbid chronic diseases.,” Ann Fam Med, vol. 1,

no. 1, pp. 15–21, 2003.

[22] V. Kemp, “Use of chronic disease self-management strategies in mental healthcare.,”

Curr. Opin. Psychiatry, vol. 24, no. 2, pp. 144–148, 2011.

[23] A. Gill, K. Kuluski, L. Jaakkimainen, G. Naganathan, R. Upshur, and W. P. Wodchis,

“‘Where do we go from here?’ Health system frustrations expressed by patients with

multimorbidity, their caregivers and family physicians,” Healthc. Policy, vol. 9, no. 4, pp.

73–89, 2014.

[24] Ministry of Health and Long Term Care, “Preventing and managing chronic disease:

Ontario’s framework,” pp. 1–50, 2007.

[25] C. Liddy, V. Blazkho, and K. Mill, “Challenges of self-management when living with

multiple chronic conditions Systematic review of the qualitative literature,” Can. Fam.

Physician, vol. 60, no. 12, pp. 1123–33, 2014.

120

[26] J. Trappenburg, N. Jonkman, T. Jaarsma, H. van Os-Medendorp, H. Kort, N. de Wit, A.

Hoes, and M. Schuurmans, “Self-management: One size does not fit all,” Patient Educ.

Couns., vol. 92, no. 1, pp. 134–137, 2013.

[27] H. L. Interventions, “RapidE  : Chronic Care.”

[28] K. Glanz, B. Rimer, and K. Viswanath, Health behavior and health education: theory,

research and practice, 4th ed. Jossey-Bass, 2008.

[29] H. J. Liss, R. L. Glueckauf, and E. P. Ecklund-Johnson, “Research on telehealth and

chronic medical conditions: Critical review, key issues, and future directions.,” Rehabil.

Psychol., vol. 47, no. 1, pp. 8–30, 2002.

[30] K. H. Bowles, D. E. Holland, and D. A. Horowitz, “A comparison of in-person home care,

home care with telephone contact and home care with telemonitoring for disease

management,” Journal of Telemedicine and Telecare, vol. 15, no. 7. pp. 344–350, 2009.

[31] S. C. Inglis, R. a Clark, and J. G. F. Cleland, “Telemonitoring in patients with heart

failure.,” N. Engl. J. Med., vol. 364, no. 11, pp. 1078–9; author reply 1079–80, 2011.

[32] D. Scherr, P. Kastner, A. Kollmann, A. Hallas, J. Auer, H. Krappinger, H. Schuchlenz, G.

Stark, W. Grander, G. Jakl, G. Schreier, and F. M. Fruhwald, “Effect of home-based

telemonitoring using mobile phone technology on the outcome of heart failure patients

after an episode of acute decompensation: randomized controlled trial,” Journal of

Medical Internet Research, vol. 11, no. 3. p. e34, 2009.

[33] F. Koehler, S. Winkler, M. Schieber, U. Sechtem, K. Stangl, M. Bohm, H. Boll, G.

Baumann, M. Honold, K. Koehler, G. Gelbrich, B.-A. Kirwan, and S. D. Anker, “Impact

of remote telemedical management on mortality and hospitalizations in ambulatory

patients with chronic heart failure: the telemedical interventional monitoring in heart

failure study,” Circulation, vol. 123, no. 17, pp. 1873–1880, 2011.

[34] E. Seto, K. Leonard, J. Cafazzo, C. Masino, J. Barnsley, and H. Ross, “Self-care and

quality of life of heart failure patients at a multidisciplinary heart function clinic,” J.

Cardiovasc. Nurs., vol. 26, no. 5, pp. 377–85, 2011.

121

[35] B. Riegel, B. Carlson, and D. Glaser, “Development and testing of a clinical tool

measuring self-management of heart failure,” Hear. Lung, vol. 29, no. 1, pp. 4–15, 2000.

[36] T. Jaarsma, “Inter-professional team approach to patients with heart failure,” Heart Lung,

vol. 91, no. 6. pp. 832–838, 2005.

[37] A. Sahebi, J. Mohammad-Aliha, M. Ansari-Ramandi, and N. Naderi, “Investigation the

relationship between self-care and readmission in patients with chronic heart failure,”

Research in cardiovascular medicine, vol. 4, no. 1. p. e25472, 2015.

[38] B. Carlson, B. Riegel, and D. K. Moser, “Self-care abilities of patients with heart failure,”

Hear. Lung J. Acute Crit. Care, vol. 30, no. 5, pp. 351–359, 2001.

[39] D. Benatar, “Outcomes of Chronic Heart Failure,” Arch. Intern. Med., vol. 163, no. 3, p.

347, 2003.

[40] L. R. Goldberg, J. D. Piette, M. N. Walsh, T. A. Frank, B. E. Jaski, A. L. Smith, R.

Rodriguez, D. M. Mancini, L. A. Hopton, E. J. Orav, and E. Loh, “Randomized trial of a

daily electronic home monitoring system in patients with advanced heart failure: the

Weight Monitoring in Heart Failure (WHARF) trial,” Am. Heart J., vol. 146, no. 4, pp.

705–712, 2003.

[41] J. G. F. Cleland, A. A. Louis, A. S. Rigby, U. Janssens, and A. H. M. M. Balk,

“Noninvasive home telemonitoring for patients with heart failure at high risk of recurrent

admission and death,” J. Am. Coll. Cardiol., vol. 45, no. 10, pp. 1654–1664, 2005.

[42] J. L. Roglieri, R. Futterman, K. L. McDonough, G. Malya, K. R. Karwath, D. Bowman, J.

Skelly, and S. W. Warburton, “Disease management interventions to improve outcomes in

congestive heart failure,” American Journal of Managed Care, vol. 3, no. 12. pp. 1831–9,

1997.

[43] R. S. Schofield, S. E. Kline, C. M. Schmalfuss, H. M. Carver, J. M. Aranda, D. F. Pauly,

J. A. Hill, B. I. Neugaard, and N. R. Chumbler, “Early outcomes of a care coordination-

enhanced telehome care program for elderly veterans with chronic heart failure,” Telemed.

J. e-Health, vol. 11, no. 1, pp. 20–27, 2005.

122

[44] R. A. Clark, S. C. Inglis, F. . McAlister, J. G. . Cleland, and S. Stewart, “Telemonitoring

or structured telephone support programmes for patients with chronic heart failure:

systematic review and meta-analysis,” BMJ Open, vol. 334, no. 7600, pp. 942–942, 2007.

[45] K. H. Bowles and A. C. Baugh, “Applying Research Evidence to Optimize

Telehomecare,” Journal of Cardiovascular Nursing, vol. 22, no. 1. pp. 5–15, 2007.

[46] C. D. Mathers, C. Stein, D. M. Fat, C. Rao, M. Inoue, N. Tomijima, C. Bernard, A. D.

Lopez, and C. J. L. Murray, “Global burden of disease 2000: version 2 methods and

results.,” Public Health, no. 50, p. 108, 2002.

[47] M. Zwerink, M. Brusse-Keizer, P. D. L. P. M. van der Valk, G. A. Zielhuis, E. M.

Monninkhof, J. van der Palen, P. a Frith, and T. Effing, “Self management for patients

with chronic obstructive pulmonary disease,” Cochrane Database Syst. Rev., vol. 3, no. 3,

2014.

[48] J. Bourbeau, M. Julien, F. Maltais, M. Rouleau, A. Beaupre, and R. Singh, “Reduction of

hospital utilization in patients with chronic obstructive pulmonary disease,” Arch. Intern.

Med., vol. 163, no. September 2015, pp. 585–91, 2003.

[49] C. E. Bolton, C. S. Waters, S. Peirce, and G. Elwyn, “Insufficient evidence of benefit: a

systematic review of home telemonitoring for COPD,” J. Eval. Clin. Pract., vol. 17, no. 6,

pp. 1216–1222, 2011.

[50] P. W. Jones, G. Harding, P. Berry, I. Wiklund, W.-H. Chen, and N. Kline Leidy,

“Development and first validation of the COPD Assessment Test,” Eur. Respir. J., vol. 34,

no. 3, pp. 648–654, 2009.

[51] A. Levey, R. Atkins, J. Coresh, E. Cohen, A. Collins, K.-U. Eckardt, M. E. Nahas, B.

Jaber, M. Jadoul, A. Levin, N. Powe, J. Rossert, D. Wheeler, N. Lameire, and G.

Eknoyan, “Chronic kidney disease as a global public health problem: approaches and

initiatives – a position statement from kidney disease improving global outcomes,” Kidney

Int., vol. 72, no. 3, pp. 247–259, 2007.

123

[52] A. Levin, B. Hemmelgarn, B. Culleton, S. Tobe, P. McFarlane, M. Ruzicka, K. Burns, B.

Manns, C. White, F. Madore, L. Moist, S. Klarenbach, B. Barrett, R. Foley, K. Jindal, P.

Senior, N. Pannu, S. Shurraw, A. Akbari, A. Cohn, M. Reslerova, V. Deved, D.

Mendelssohn, G. Nesrallah, J. Kappel, and M. Tonelli, “Guidelines for the management of

chronic kidney disease.,” CMAJ, vol. 179, no. 11, pp. 1154–1162, 2008.

[53] R. Hopkins, A. Garg, A. Levin, A. Molzah, C. Rigatto, J. Singer, G. Soltys, S. Soroka, P.

Parfrey, B. Barrett, and R. Goeree, “Cost-effectiveness analysis of a randomized trial

comparing care models for chronic kidney disease,” Clin. J. Am. Soc. Nephrol., vol. 6, no.

6, pp. 1248–1257, 2011.

[54] DaVita, “Chronic Kidney Disease Stages & Living with CKD - DaVita.” .

[55] S. H. Chen, Y. F. Tsai, C. Y. Sun, I. W. Wu, C. C. Lee, and M. S. Wu, “The impact of

self-management support on the progression of chronic kidney disease - a prospective

randomized controlled trial,” Nephrol. Dial. Transplant., vol. 26, no. 11, pp. 3560–3566,

2011.

[56] A. M. El Nahas and A. K. Bello, “Chronic kidney disease: the global challenge,” Lancet,

vol. 365, no. 9456, pp. 331–340, Sep. 2015.

[57] M. T. Blinkhorn, “Telehealth in nephrology health care: a review,” Ren. Soc. Australas. J.,

vol. 8, no. 3, pp. 132–139, 2012.

[58] International Diabetes Federation, “Diabetes Atlas | International Diabetes Federation,”

Diabetes Atlas. 2012.

[59] C. D. Association, “An economic tsunami,” Can. Diabetes Assoc., no. December, pp. 1–

13, 2010.

[60] P. H. A. of Canada, “Chapter 2 – The health impact of diabetes on Canadians - diabetes in

Canada: facts and figures from a public health perspective - public health agency of

Canada.” 2011.

124

[61] L. E. Egede, M. Gebregziabher, C. E. Dismuke, C. P. Lynch, R. N. Axon, Y. Zhao, and P.

D. Mauldin, “Medication nonadherence in diabetes: longitudinal effects on costs and

potential cost savings from improvement,” Diabetes Care, vol. 35, no. 12, pp. 2533–2539,

2012.

[62] M. I. Harris, H. National, and S. Nutrition Examination, “Frequency of blood glucose

monitoring in relation to glycemic control in patients with type 2 diabetes,” Diabetes

Care, vol. 24, no. 6, pp. 979–982, 2001.

[63] W. H. Polonsky, “Structured self-monitoring of blood glucose significantly reduces A1c

levels in poorly controlled, noninsulin-treates type 2 diabetes,” Diabetes Care, vol. 34, pp.

262–267, 2011.

[64] M. S. Marcolino, J. X. Maia, M. B. M. Alkmim, E. Boersma, and A. L. Ribeiro,

“Telemedicine application in the care of diabetes patients: systematic review and meta-

analysis,” PLoS One, vol. 8, no. 11, p. e79246, 2013.

[65] A. M. Delamater, “Improving patient adherence,” Clin. Diabetes, vol. 24, no. 2, pp. 71–

77, 2006.

[66] A. G. Logan, “Transforming hypertension management using mobile health technology

for telemonitoring and self-care support,” Can. J. Cardiol., vol. 29, no. 5, pp. 579–585,

2013.

[67] P. S. Garimella and K. Uhlig, “Current issues in the management and monitoring of

hypertension in chronic kidney disease,” Current Opinion in Nephrology and

Hypertension, vol. 22, no. 6. pp. 599–606, 2013.

[68] C. G. Weaver, F. M. Clement, N. R. C. Campbell, M. T. James, S. W. Klarenbach, B. R.

Hemmelgarn, M. Tonelli, and K. a. McBrien, “Healthcare Costs Attributable to

HypertensionNovelty and Significance,” Hypertension, vol. 66, no. 3, pp. 502–508, 2015.

125

[69] K. Sivakumaran, D; Earle, “Telemonitoring: use in the management of hypertension.,”

Vascular health and risk management, vol. 10. pp. 217–24, 2014.

[70] T. Kaihara, K. Eguchi, and K. Kario, “Home BP monitoring using a telemonitoring

system is effective for controlling BP in a remote island in Japan,” J. Clin. Hypertens.,

vol. 16, no. 11, pp. 814–819, 2014.

[71] F. McCant, G. McKoy, J. Grubber, M. K. Olsen, E. Oddone, B. Powers, and H. B.

Bosworth, “Feasibility of blood pressure telemonitoring in patients with poor blood

pressure control.,” J. Telemed. Telecare, vol. 15, pp. 281–285, 2009.

[72] J. Hanley, J. Ure, C. Pagliari, a. Sheikh, and B. McKinstry, “Experiences of patients and

professionals participating in the HITS home blood pressure telemonitoring trial: a

qualitative study,” BMJ Open, vol. 3, no. 5, pp. e002671–e002671, 2013.

[73] A. Darkins, P. Ryan, R. Kobb, L. Foster, E. Edmonson, B. Wakefield, and A. Lancaster,

“Care coordination/home telehealth: the systematic implementation of health informatics,

home telehealth, and disease management to support the care of veteran patients with

chronic conditions,” Telemed. e-Health, vol. 14, no. 10, pp. 1118–1126, 2008.

[74] P. Y. Takahashi, G. J. Hanson, J. L. Pecina, R. J. Stroebel, R. Chaudhry, N. D. Shah, and

J. M. Naessens, “A randomized controlled trial of telemonitoring in older adults with

multiple chronic conditions: the Tele-ERA study,” BMC Health Serv. Res., vol. 10, p. 255,

2010.

[75] P. Y. Takahashi, J. Pecina, B. Upatising, R. Chaudhry, N. D. Shah, H. Van Houten, S.

Cha, I. Croghan, and J. M. Naessens, “A randomized controlled trial of telemonitoring in

older adults with multiple health issues to prevent hospitalizations and emergency

department visits telemonitoring in older adults,” Arch. Intern. Med., vol. 172, no. 10, p.

773, 2012.

[76] H. C. Noel, D. C. Vogel, J. J. Erdos, D. Cornwall, and F. Levin, “Home Telehealth

Reduces Healthcare Costs,” Telemed. J. e-Health, vol. 10, no. 2, pp. 170–183, 2004.

126

[77] A. Kwan, “Using mobile technologies for healthier aging,” mHealth Alliance, United

Nations Found., pp. 1–22, 2012.

[78] “MedDiary - Personal Health Management System,” 2015. [Online]. Available:

http://meddiary.com/.

[79] Centre for Global eHealth Innovation, “Medly,” 2015. [Online]. Available:

http://ehealthinnovation.org/what-we-do/.

[80] D. Rubin, J., & Chisnell, “Handbook of usability testing [electronic resource]  : How to

plan, design, and conduct effective tests (2nd ed.),” Indianapolis, Wiley Pub., p. 386,

2008.

[81] R. Priester, R. L. Kane, and A. M. Totten, “How the Current System Fails People With

Chronic Illnesses,” pp. 1–19, 2005.

[82] K. Kuluski, A. Gill, G. Naganathan, R. Upshur, R. L. Jaakkimainen, and W. P. Wodchis,

“A qualitative descriptive study on the alignment of care goals between older persons with

multi-morbidities, their family physicians and informal caregivers,” BMC Fam. Pract.,

vol. 14, no. 1, p. 133, 2013.

[83] G. Naganathan, K. Kuluski, A. Gill, L. Jaakkimainen, R. Upshur, and W. P. Wodchis,

“Perceived value of support for older adults coping with multi-morbidity: patient, informal

care-giver and family physician perspectives,” Ageing Soc., pp. 1–24, 2015.

[84] N. Schadewitz and T. Jachna, “Comparing inductive and deductive methodologies for

design patterns identification and articulation,” pp. 1–19, 2007.

[85] M. Hassali, M. Atif, F. Saleem, and A. Shafie, “Drug attitude and adherence: A qualitative

insight of patients with hypertension,” J. Young Pharm., vol. 4, no. 2, p. 101, 2012.

[86] I. D. Foundation, “Support Users by Being Consistently Consistent  » Interaction Design

Foundation,” 2015. [Online]. Available: https://www.interaction-

design.org/literature/article/support-users-by-being-consistently-consistent.

127

[87] Android, “Action Bar | Android Developers.” 2013.

[88] WebMD Inc., “High Blood Pressure Symptoms,” 2015. [Online]. Available:

http://www.webmd.com/hypertension-high-blood-pressure/guide/hypertension-symptoms-

high-blood-pressure. [Accessed: 15-Jul-2015].

[89] “Impact of CKD in Ontario,” Ontario Renal Network, 2014. [Online]. Available:

http://www.renalnetwork.on.ca/info_for_patients/impact_of_ckd/#.VifXsxCrRME.

[90] M. Fortin, J. Haggerty, J. Almirall, T. Bouhali, M. Sasseville, and M. Lemieux, “Lifestyle

factors and multimorbidity: a cross sectional study,” BMC Public Health, vol. 14, pp. 1–8,

2014.

[91] A. Audulv, K. Asplund, and K. Norbergh, “The integration of chronic illness self-

management,” Qual. Health Res., vol. 22, no. 3, pp. 332–345, 2012.

[92] M. E. Hilliard, A. Hahn, A. K. Ridge, M. N. Eakin, and K. A. Riekert, “User Preferences

and Design Recommendations for an mHealth App to Promote Cystic Fibrosis Self-

Management.,” JMIR mHealth uHealth, vol. 2, no. 4, p. e44, Jan. 2014.

[93] R. Gallagher, J. Donoghue, L. Chenoweth, and J. Stein-Parbury, “Self-management in

older patients with chronic illness,” Int. J. Nurs. Pract., vol. 14, no. 5, pp. 373–382, 2008.

[94] C. Duguay, F. Gallagher, and M. Fortin, “The unique experience of adults with

multimorbidity: a qualitative study,” J. Comorbidity, vol. 4, no. 1, pp. 11–21, 2014.

[95] R. Walker, M. R. Marshall, and N. Polaschek, “Improving self-management in chronic

kidney disease  : a pilot study,” vol. 9, no. 3, pp. 116–125, 2013.

[96] N. E. Schoenberg, S. H. Bardach, K. N. Manchikanti, and A. C. Goodenow, “Appalachian

residents’ experiences with and management of multiple morbidity.,” Qualitative Health

Research, vol. 21, no. 5. pp. 601–611, 2011.

128

[97] C. Vogeli, A. E. Shields, T. A. Lee, T. B. Gibson, W. D. Marder, K. B. Weiss, and D.

Blumenthal, “Multiple chronic conditions: prevalence, health consequences, and

implications for quality, care management, and costs,” Journal of General Internal

Medicine, vol. 22, no. 3. pp. 391–395, 2007.

[98] A. K. Schaink, K. Kuluski, R. F. Lyons, M. Fortin, A. R. Jadad, R. Upshur, and W. P.

Wodchis, “A scoping review and thematic classification of patient complexity: offering a

unifying framework,” J. Comorbidity, vol. 2, no. 1, pp. 1–9, 2012.

[99] K. Lorig, P. L. Ritter, and K. Plant, “A disease-specific self-help program compared with

a generalized chronic disease self-help program for arthritis patients,” Arthritis Care Res.,

vol. 53, no. 6, pp. 950–957, 2005.

[100] H. Blake, “Mobile phone technology in chronic disease management,” Nurs. Stand., vol.

23, no. 12, pp. 43–46, 2008.

[101] M. Q. Patton, “Enhancing the quality and credibility of qualitative analysis.,” Health Serv.

Res., vol. 34, no. 5 Pt 2, pp. 1189–1208, 1999.

[102] V. Jupp, “The SAGE dictionary of social research methods.” Sage Publications, London,

2006.

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Appendices

Appendix A – Sample of Designs

Following are a sample of various designs that were created. Although the main features

remained intact through the process (ex. alert messages, measured readings, instructions on

measurements to take, etc.), there were many changes in the designs of these features.

Main Components of the MCC App

Figure 25: Components of the main page of MCC app wireframe in default mode.

Figure 26: Main page of the MCC app wireframe after measurements have been recorded.

Figure 27: Wireframe for timeline of events. It contains a history of alerts and major events.

Figure 28: Details page pertaining to the parameter, blood glucose.

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Guided Wizard Designed in November 2014

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Checklist Format of the Main Page

Figure 29: November 2014 checklist format.

Figure 30: December 2014 checklist format.

Figure 31: February 2015 checklist format.

Figure 32: March 2015 checklist format in grid view.

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Wireframes that were created on PowerPoint were transformed into higher fidelity designs, as

shown in images below:

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Appendix B – Pre-Study Questionnaires

1. In what age range do you belong? (check one box) ¨ 18 – 39 years old ¨ 40 – 64 years old ¨ 65 years old or over

2. Please select your gender: ¨ Male ¨ Female

3. What is your highest level of education completed? ¨ Elementary School ¨ High School ¨ College/Undergraduate Study ¨ Post-Graduate Study ¨ Other

4. Do you use glasses (or contact lenses) for distance? ¨ Yes ¨ No

5. Do you use glasses (or contact lenses) for reading? ¨ Yes ¨ No

6. Do you use a Smartphone (excluding regular cell phones)? ¨ Yes ¨ No è Please proceed to Question 11

7. How comfortable are you with using a Smartphone? ¨ Not comfortable ¨ Somewhat comfortable ¨ Comfortable ¨ Very comfortable

8. What type of Smartphone do you use? ¨ Blackberry ¨ iPhone ¨ HTC ¨ Samsung ¨ Motorola ¨ Other (please specify): ______________

9. Please estimate how often you use your Smartphone: ¨ Frequently (a few times a day) ¨ Sometimes (a few times a week) ¨ Rarely (a few times a month) ¨ Never

10. Please indicate the activities you use your Smartphone for: ¨ Email ¨ Information seeking (e.g., finding addresses or directions) ¨ Scheduling (e.g., to-do lists, appointments) ¨ Information storage (e.g., contacts) ¨ Recreation (e.g., text messaging) ¨ Other: ______________

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11. Do you use a cell phone? ¨ Yes ¨ No è Please proceed to Question 15

12. Please estimate how often you use your cell phone: ¨ Frequently (a few times a day) ¨ Sometimes (a few times a week) ¨ Rarely (a few times a month) ¨ Never

13. What features do you use on your cell phone? Check all that apply. ¨ Voice calls ¨ Text messaging ¨ Web browsing ¨ Other (please specify): ______________

14. Do you use Wi-Fi or Data on your cell phone? ¨ Yes (please specify): ______________ ¨ No

15. Do you use a desktop or laptop computer? ¨ Yes ¨ No è End of questionnaire

16. Please estimate how often you use your desktop or laptop: ¨ Constantly (several times a day) ¨ Frequently (a few times a day) ¨ Sometimes (a few times a week) ¨ Rarely (a few times a month) ¨ Never

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Appendix C – Post-Study Questionnaires

1. Overall, how easy was it to use the application? Very Difficult Very Easy

1 2 3 4 5

2. How easy was it to access the application? Very Difficult Very Easy

1 2 3 4 5

3. How easy was it to navigate through the application? Very Difficult Very Easy

1 2 3 4 5

4. How easy was it to search for and review information? Very Difficult Very Easy

1 2 3 4 5

5. How easy was it to add new information? Very Difficult Very Easy

1 2 3 4 5

6. How easy was it to edit entries? Very Difficult Very Easy

1 2 3 4 5

7. How easy was it to correct mistakes? Very Difficult Very Easy

1 2 3 4 5

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8. Please circle the rating that best represents your opinion about the various components of the device:

Very

Unsatisfied Very

Satisfied Application readability 1 2 3 4 5 Size of characters on screen 1 2 3 4 5

Language/Wording 1 2 3 4 5 Amount of information on screen 1 2 3 4 5

Visual Look/Layout 1 2 3 4 5 Sequence of screens 1 2 3 4 5 Application speed 1 2 3 4 5 Size of buttons 1 2 3 4 5 Shape of buttons 1 2 3 4 5 Meaning of icons 1 2 3 4 5 Size of icons 1 2 3 4 5

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Appendix D – Clinician Interview Guide Cluster of Chronic Conditions to Target

1. We have some ideas of chronic diseases we want to target, but we want to know your opinion on this matter. For people with MCC, which chronic diseases are most commonly seen together that would benefit from the use of a mobile phone app?

2. What is your role in providing care for the patients with MCC?

3. In your opinion, should we address CKD, CHF, COPD and diabetes simultaneously in one mobile app?

4. There is a variation in the severity of the health conditions. What type of patients do you

think would benefit the most from an app like ours? Mild or severe cases? Goals of Care for MCC (Data that patients should self-manage)

5. For people with MCC, what do you think are the top 2 most important factors that need to be monitored for CHF? CKD? COPD? Diabetes Type II? (go through each of the 4 diseases in the table individually)? • Cue: For example, for diabetes, we monitor the blood glucose.

HF CKD COPD Diabetes Self-care

6. We don't want to overburden patients by asking them to collect too much information for

each of their conditions. In terms of MCC in general, which of these factors are absolutely necessary for self-management? • Cue: How important would it be to have a medications list on the app?

o How would this information be useful to the patients? o Can you tell me a bit about how medication changes are made? o How do you determine the correct dose for the different diseases? o How are the patients currently made aware of this?

• Cue: How important would it be to have lab values? • Cue: How important would it be to have symptoms monitoring? • Cue: How important would it be to have training modules

7. What are some current challenges that you as a clinician experience when providing care for patients managing multiple chronic illnesses? (Particularly for patients with heart failure, CKD, diabetes and COPD)

• Cue: Such as conflicting advice for different conditions or coordination of information among different providers.

o How do you determine the ideal value ex. blood pressure?

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o What do you do if there is a difference is the target values between the different health conditions?

• Scenario: What conflicts occur between CKD and CHF patient? o What actions do clinicians take to resolve the issue? o What actions can patients take to manage their conditions?

What type of healthcare model does this fit into?

8. How do you currently monitor your patients with MCC? • What is the current workflow in your clinic for getting alerts from patients? • What actions do you take in your clinic when you get an alert?

9. Let’s say that our system has the ability to send an alert if it notices that the patient’s

health is deteriorating (ex. extremely high blood pressure). Who should these alerts be sent to? Specialists or primary caregiver? Other?

10. How would these alerts be useful to the care team? 11. Who should be responsible for arranging follow up phone calls or visits once an alert is

issued? Perception of the Proposed Self-Management System

12. What are your general thoughts about this system? Do you think a remote monitoring mobile app such as ours can be helpful for managing multiple chronic illnesses?

13. How does this self-management app fit into clinical management?

14. What would prevent you from using the system in your practice? • Cue: What barriers do use see?

15. How can we make the system better suited to you and your patients’ needs? • Please list top three things we need to include in the mobile app that will be useful for

patients with multiple chronic conditions. • What are top three things we can include in the mobile app that will be useful for

clinicians? Thank you so much for your input. If the opportunity arose again, would it be okay if we contact you again for additional advice? Also as we move forward with this study would you be willing and/or interested in participating in ongoing research meetings to contribute ideas for future studies?

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Appendix E – Patient Interview Guide

Hi my name is ________. I am a Master’s student and part of a research team at UHN and MSH.

We are developing a mobile phone application that would allow patients to manage their chronic health conditions. Therefore we would like to get input from people who have two or more health conditions. (We are looking for people who have combinations of diabetes, hypertension, congestive heart failure and chronic obstructive pulmonary disease.)

During our interview session, I will be asking you questions about how you currently manage your conditions and what features we could possibly include to the app to make it useful for you. You may stop the interview at any time, for any reason, and this will not affect your care. We will spend about 30 minutes together. If you become tired or need a break, we can stop the interview anytime and I can come back at another time to finish our interview.

Patient Engagement and Background Questions Life and health care experiences are unique for each individual. I would like to begin the interview by learning more about your personal experience. 1) Can you tell me a bit about your current health? [Cues: What conditions do you have? When were you diagnosed? etc.] 2) What do you find difficult about managing your health conditions? [Cues: For example, are there any aspects of self-management that you find frustrating or inefficient?] • Do you have any difficulties managing your health conditions? [Cue: If yes, can you please

describe what you find difficult.] 3) What are some day-to-day activities you do to help you manage your conditions? 4) Can you please describe a normal day in your life? [e.g. Wake up, shower, breakfast, take meds, go to work, lunch, finish work, go to park, take meds, have dinner at home, meds and sleep].

Care Provided by Family Doctors

5) Is there someone who organizes your care? Is someone overseeing your care plan? Please describe. [Cue: family doctor?] 6) Do you feel like the care you receive at your family doctors’ office helps with your overall health condition(s)? Is everything being done at your doctors’ office helping you? □ Yes (explain) □ No (explain) 7) Can you tell me what might help you with your health conditions?

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Medications and Treatments I would like to learn more about the treatments or medications that you may be taking to address your health conditions and any related symptoms. This may include pills, injections, patches, intravenous therapy, hospital procedures such as dialysis. 8) Are you currently taking any medications?

□ Yes □ No □ Don’t know 9) Do you experience any difficulties with having to take your medications?

Cue: If yes, what do you find challenging about taking your medications?

10) Have you experienced any bad reactions or bad symptoms due to your medications? □ Yes □ No □ Don’t know If yes, how did you deal with it?

11) How do you deal with changes in medications? a) Who instructs you to change the medications or dosage? [Cue: Family doctor?

Specialists?] b) Have you experienced any conflicts in your medication instructions from different

doctors? If yes, please explain. c) What is usually the reason behind the changes in medications? [e.g. Adverse events,

symptoms?] [Cue: How often do your medications change?] 12) Do you update your family doctor and specialists about the changes in medications? [e.g.

□ Yes (how? when?) □ No (why?) 13) How do you keep track of all the medications you need to take? Cue: Do you use pillboxes, calendars, notes, whiteboards, alarms? 14) Does someone help you with your medications? (e.g. reminders, help with taking/injecting)

□ Yes (Whom? How?) □ No

a) If no, do you need assistance when taking your medications? □ Yes (how? what?) □ No □ Don’t know

Symptoms I would like to learn more about the symptoms you experience and what would help you in managing these symptoms. 15) a. Can you describe some of the symptoms you have experienced in the past 6 months?

b. Which of your health conditions do you associate these symptoms to?

16) What actions do you take when you experience any type of symptoms?

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17) Do you contact anyone when you have these symptoms? [If yes, ask:]: Who do you contact about your symptoms?

18) How do you track your symptoms?

19) What do you find challenging about managing your symptoms? 20) What will help you in managing your symptoms better? Care Needs and Goals I would like to learn about your care and your goals of care. 21) What are your goals of care? In other words, what would you say are your most important

goals for: doing the things you want to do, staying in the best health that you can attain, and living the life that you believe you can live?

22) I would like to know who you would say is important to help you do the things you want to do and stay in the best health that you can attain:

[Circle the value that fits]

Not Important

A little Important

Important Very Important

Critical

Family doctor ‘your main doctor’ 1 2 3 4 5

Home care (CCAC) 1 2 3 4 5 Family caregivers 1 2 3 4 5 Specialist doctors (e.g. cardiologist, psychiatrist)

1 2 3 4 5

23) Would you say that these different people communicate to you? Do they understand your goals of care? 24) Do you experience any frustration in achieving your health goals of care? Please explain. [Cues: Health system; social support; individual actions etc.].

25) Do you receive conflicting instructions from the different healthcare providers? [Cue: Medications, diet, fluid intake]. [if yes, ask]:

a. How do you deal with conflicting instructions from your healthcare providers?

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Personality and Technology 26) Are you comfortable using technologies? [Cue: How comfortable are you with using new and upcoming technology?] □ Yes □ No

27) Do you own any devices such as a computer, tablet, smartphone, cellphone? • If Yes, what do you own? • Do you use any apps on your cellphone? If yes, which is your favorite and why?

28) Do you use any of these devices to help you manage your conditions? [ex. remember taking your medications or keeping track of any symptom]

29) Do you look to outside sources such as internet or books to find more information about your conditions?

• If yes, what type of information do you look for? 30) As we move forward with this study would you be willing and/or interested in participating in ongoing research meetings to contribute ideas for future studies? Thank you for taking the time to participate in this survey. You are helping us a lot. We really appreciate it.

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Appendix F – Product Requirements

Product requirements provided details on the user requirements for the MCC smartphone application. It was one of the documents prepared in order to ensure the process of design and development followed the guidelines of ISO 13485 quality management system. A total of five documents were prepared for ISO 13485 requirements.

• Design and Development • Hazard Analysis • Medical Device Assessment • Product Requirements • Traceability Matrix

Product Requirements 1. Introduction 1.1 Purpose and Intended Audience The purpose of Medly MCC Product Requirements Document is to provide details about the business and user requirements in language suitable for a non-technical audience. It also forms the basis for validation testing. This document does not cover details on the design or implementation of Medly MCC app, but the objective is to provide an overview including definitions, goals, objectives, context, and major capabilities. The Product Requirements Document formally specifies requirements including:

• Functional (user) requirements. • Non-Functional requirements. • Out of Scope requirements.

The intended audience of the Product Requirement Document includes the main project stakeholders:

• Centre for Global eHealth Innovation • Toronto Western Hospital Family Health Team • Mount Sinai Hospital Family Health Team

2 Description of the Product 2.1 Intended Use The Medly MCC app is a software health application to be used by adults with multiple chronic conditions, including combinations of HTN, COPD, CHF, DM and HTN. This app is intended to help individuals self-manage their diseases and to improve clinical management. The Medly MCC app will collect user-entered MCC information such as symptoms and measurements such as blood pressure, weight and blood glucose. These measurements can be collected wirelessly using commercially available Bluetooth enabled blood pressure monitor, weight scale and glucometer. User medication lists can also be transferred to the app via the Medly Dashboard.

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The Medly Dashboard is a web interface where their healthcare team participating in the MCC program can enter patient data. The app will use this information to generate messages to the user to encourage self-management of their disease, which in turn will lead to improved health outcomes. The app can also alert the clinician to critical values in blood pressure, blood glucose, weight and symptoms. Medly Dashboard is the web interface that is intended to be used by clinicians to monitor the patient’s symptoms remotely. 2.2 User Environments The Medly MCC app is intended to be used on an individual’s smartphone at home or in the clinic. The app can interface with home Bluetooth medical devices, such as blood pressure monitor, weight scales and glucometers. Data will be sent to a data store, which is accessed by clinicians through the web interface called Medly Dashboard. Clinical data will be entered and updated by the clinicians such as those in the Family Health Teams, also through the Medly Dashboard.

Figure 1: Context diagram of the app illustrating product and external interfaces. 2.3 Intended Users The Medly MCC app is a consumer application intended to be used by patients with MCC, such as combinations of HTN, CHF, COPD, DM, HTN. An initial feasibility pilot is planned. As well, service personnel supporting the Medly MCC app will also have access to the application. 2.4 Expected Lifetime of the Device The Medly MCC app is a software only product. There is expected lifetime of 5 years for any of the project components. The product will be serviced at minimum until the pilot feasibility study is concluded. 2.5 General Constraints Items that will limit product design options include:

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• Regulations and policies outlined in the Canadian Privacy Act and Ontario Personal Health Information Protection Act

• Lack of standard clinical practice guidelines for management of multiple chronic conditions. 3 Functional Requirements (User Requirements) Section 3.1 Requirement Group 1 – User Smartphone application REQ. # I.D. Requirement Description Mobile Interface User_Req_1 Users shall be able to start, restart, or shutdown the app when requested on

their mobile device. User_Req_2 Users shall only view parameters that are specific to their chronic health

conditions (one or more of CHF, COPD, DM, and/or HTN). User_Req_3 Users shall be able to transfer physiological measurements such as weight,

blood pressure and blood glucose into the application using external devices. User_Req_4 Users shall be able to view their physiological parameters such as weight,

blood pressure and blood glucose. User_Req_5 Users shall be able to view their target range for the measured physiological

parameters (weight, blood pressure, blood glucose) User_Req_6 Users shall be able to record symptoms through a series of clinically guided

questions. User_Req_7 Users shall receive automated reminders if data has not been entered, or new

readings already available. User_Req_8 Users shall be able to receive automated instructions or alerts based on their

symptoms and physiological measures. User_Req_9 Users shall be able to view trends for symptoms and physiological

measurements: blood pressure, blood glucose and weight. User_Req_10 Users shall be able to view history for symptoms and physiological

measurements: blood pressure, blood glucose and weight. User_Req_11 App shall send an alert to the dashboard. User_Req_12 Users shall be able to view their care team contact information.

4 Non-Functional Requirements

4.1 Hardware Requirements REQ. # I.D. Requirement Description Hardware_Req_1 Client shall have Samsung Galaxy Core (Bluetooth capability on

smartphone). Hardware_Req_2 Bluetooth-enabled peripherals:

• Blood Pressure/Pulse cuff • Weight Scale • Glucometer

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4.2 Software Requirements REQ. # I.D. Requirement Description Software_Req_1 Mobile device shall support minimum Android 4.3. Software_Req_2 Medly MCC app requires an interface to transfer physiological readings to the

server. Software_Req_3 Medly MCC requires a server to store and process readings. Software_Req_4 Medly MCC requires access to an email server to send emails to the clinician. 4.3 Security Requirements REQ. # I.D. Requirement Description Sec_Req_1 Medly MCC shall ensure that authorized modifications during maintenance will

not inadvertently allow unauthorized individuals access to the system. Sec_Req_2 Medly MCC shall be protected behind firewalls against malware. Sec_Req_3 Medly MCC shall use a secure authentication method to authenticate and

connect to dashboard. Sec_Req_4 Medly MCC shall securely store user login information. Sec_Req_5 User information shall be private and secure.

4.4 Usability Requirements REQ. # I.D. Requirement Description Usability_Req_1 Medly MCC shall support language in English. Usability_Req_2 The client’s user interface shall be designed in accordance with the

appropriate mobile platform-specific design guidelines, to wit: Android Official UI Guidelines: http://developer.android.com/guide/practices/ui_guidelines/index.html Android Design Patterns: Interaction Design Solutions for Developers book (by Nudelman, Greg): http://www.amazon.com/Android-Design-Patterns-Interaction-Developers/dp/1118394151

4.5 Performance Requirements REQ. # I.D. Requirement Description Perform_Req_1 Medly MCC shall provide a user experience comparable in visual design and in

response speed to commercially available applications. 4.6 Scalability Requirements REQ. # I.D. Requirement Description Scale_Req_1 Medly MCC shall support a maximum of 1 user per installation on 1 mobile

device. Scale_Req_2 Medly MCC shall support up to a minimum of 25 users at one time.

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4.7 System Interface Requirements REQ. # I.D. Requirement Description SI_Req_1 Medly MCC shall support the secure retrieval and transmission of information

over the Internet. SI_Req_2 Medly MCC shall support necessary rules-based logic or algorithms. SI_Req_3 Data (where applicable) must have the correct label type, value, units of

measurement, and timestamp. SI_Req_4 Medly MCC shall communicate with the Medly Dashboard. 4.8 Database Requirements REQ. # I.D. Requirement Description DB_1 User’s information shall be locally stored on Medly MCC app. DB_2 User’s information shall be locally stored on Medly Dashboard server. 4.9 Physical Requirements There are no physical requirements. This is a software only product. 4.10 Clinical Requirements There are no sterility, toxicity and biocompatibility requirements. This is a software only project. 4.11 Environmental Requirements There are no environmental requirements. This is a software only product. 4.12 Documentation Requirements REQ. # I.D. Requirement Description Doc_Req_1 The application shall have a user manual in English.

4.13 Manufacturing Needs and Requirement There are no manufacturing, assembly, packaging, storage, or product reusability or disposability requirements. This is a software only product. 4.14 Service Needs and Requirements REQ. # I.D. Requirement Description Service_Req_1 The application shall include an error handling system. The Centre for Global eHealth Innovation will support the application for the duration of the feasibility study. 4.15 Labeling, Packaging and Storage Requirements REQ. # I.D. Requirement Description REQ 1. The application shall follow guidance on labeling of Medical Devices under

Health Canada’s Sections 21 to 23 of the Medical Devices Regulations. Labels (such as manufacturer name and support number) will be in English and French language and presented within the user interface.

There are no packaging or storage requirements.

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4.16 Statutory and Regulatory Requirements • Medly MCC app shall comply with ISO13485 and Health Canada Medical Devices

Regulations.

5 Requirement out of SCOPE 5.1 Out of Scope • MCC app need not be compatible with other mobile phone operating systems and devices at

this time. • MCC app need not include patient-initiated e-scheduling, e-consults, and renewal of

prescriptions. • Medly MCC app need not have user interfaces, viewers or other tools within primary care

clinical data repositories or provider portals.

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Appendix G – Feature Files

Based on the user requirements shown in the Appendix F (Product Requirements), user stories

were written to describe the features from the perspective of the user of the system.

Programming of the MCC smartphone application was done on the basis of the user stories.

User stories were updated iteratively throughout the project as changes were made to the features

based on discussions with developers, designers and members of the PHIT team as well as

feedback from end-users. Following section contains a three sample feature files out of the total

of fifteen.

Feature 14119 – Disease specific parameters Product Requirement: User shall only view parameters specific to their diseases on the main page. User Story: User views disease-specific parameters on the main page As a user I only want to view parameters related to my diseases on the main page So that I know what measurements to take today Scenario 1: As a CHF patient, I shall view only symptoms, weight, and blood pressure. Given that the patient has CHF When patient launches the app Then the application should display symptoms, weight and blood pressure on the main page. Scenario 2: As a HTN patient, I shall view only blood pressure. Given that the patient has HTN When patient launches the app Then the application should display blood pressure on the main page. Scenario 3: As a COPD patient, I shall view only symptoms. Given that the patient has COPD When patient launches the app Then the application should display symptoms on the main page. Scenario 4: As a DM patient, I shall view only blood glucose. Given that the patient has DM When patient launches the app Then the application should display blood glucose on the main page. Scenario 5: As a patient with two or more chronic conditions, I shall view correct combination of parameters related to my diseases. Given that the patient has certain <diseases> When the patient launches the app

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Then the application should display only <parameters> that are specific to the <diseases> on the main page. Diseases Parameters CHF+HTN Symptoms, Weight, BP CHF+COPD Symptoms, Weight, BP CHF+DM Symptoms, Weight, BP, BG HTN+COPD Symptoms, BP HTN+DM Weight, BP, BG COPD+DM Symptoms, BG CHF+DM+COPD Symptoms, Weight, BP, BG HTN+DM+COPD Symptoms, Weight, BP, BG CHF+HTN+COPD Symptoms, Weight, BP CHF+HTN+DM Symptoms, Weight, BP, BG CHF+HTN+DM+COPD Symptoms, Weight, BP, BG Feature 14293 – Readings page latest measurements User Story: User views the latest measurements of today on the readings page. As a user I want to see the latest measurements on the readings page So that I immediately know what actions to take today Scenario 1: Readings page, no readings recorded today Given that the user navigates to the readings page And a reading and units has not been captured for today Then the parameter tile will display the icon and <timestamp> of when the last reading was captured Condition | <timestamp> | Example If <=7 days | X days ago | 1 day ago If >7 days | X weeks ago | 2 weeks ago If >30 days | X months ago | 2 months ago Scenario 2: Readings page, readings recorded today Given that the user navigates to the readings page And a reading has been captured for today Then the parameter tile will display the latest reading and units for today and <timestamp> of when the latest reading was captured Condition | <timestamp> | Example If <=60 minutes | X minutes ago | 1 minute ago If >60 minutes | actual time | 6:05 pm

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User Story: User views the instructions to navigate to To-Do page. As a user I want to see some instructions guiding me to complete actions required for today So that I know what actions to take today Scenario 1: Readings page, actions yet to complete today Given that the user navigates to the readings page And the user still has actions (i.e. reading to take/alerts to acknowledge) to take care of on the to-do page Then the readings page will indicate that the user has actions to complete today And the application will allow user to navigate to the to-do page Example

Scenario 2: Readings page, actions yet to complete today Given that the user navigates to the readings page And the user has taken care of all actions on the to-do page (i.e. reading to take/alerts to acknowledge) Then the readings page will indicate that the user has completed all actions for now And the application will allow user to navigate to the to-do page

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Example

Feature 14189 – Blood pressure Bluetooth connectivity

Product Requirement: User shall be able to transfer blood pressure readings into the app using a blood pressure monitor. User Story: User takes their blood pressure readings As a user I want the application to sync with my blood pressure machine So that I can store and share my readings on the application

Scenario 1: Blood pressure machine is paired and application is running Given the application is running And the blood pressure machine is running And the blood pressure machine is paired/connected with the application When the user completes taking their blood pressure Then the application should collect the blood pressure data from the machine And the spinning sync icon should appear And a transfer confirmation should appear

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And the application should provide the user with a confirmation screen that contains the reading value And the application should store the data in its local database And the application should send the data to the Medly Dashboard Scenario 2: Bulk transfer of unsynced BP readings and application is running Given that the phone is not paired with the blood pressure machine And the blood pressure machine is running and has unsynced blood pressure readings stored on-board And the machine and the application are paired When the application is in range of the blood pressure machine Then the application should collect all new and unsynced blood pressure data from the machine And a spinning icon should appear And a transfer confirmation should appear When there are readings with today’s timestamp Then the application should provide the user with a confirmation screen that contains the latest reading value from today And the application should store the data in its local database And the application should send the data to the Medly Dashboard When there are no readings with today’s timestamp Then the application should provide the user with a syncing animation with a message that ‘your blood pressures readings have been received’ And the application should store the data in its local database And the application should send the data to the Medly Dashboard Scenario 3: Sync with the blood pressure machine via Bluetooth when the machine is in-range when the application is running Given the phone is not paired with the blood pressure machine because it is out of range And the user has launched the application The phone will continue checking whether the blood pressure machine is in range for 30 seconds When the blood pressure ma chine is in range within 30 seconds Then the phone and blood pressure machine will reconnect And all readings will be transferred automatically When the blood pressure machine is not in range within 30 seconds Then the phone and blood pressure machine will remain disconnected Scenario 4: Bluetooth is turned off when the user launches the application Given the application is running And the blood pressure machine is running And the Bluetooth is turned off When there is a Bluetooth error Then the application displays a pop up asking for permission to turn on Bluetooth If the user taps “allow” Then the phone turns on BT And the user stays on the current page

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If the user taps “deny” Then the phone does not touch the BT settings And the user stays on the current page Scenario 5: Bluetooth connection errors when the application is running Given the application is running And the blood pressure is running When there is a Bluetooth error Then the user should see a sync error message If the user taps “okay” Then the application will display troubleshooting steps Possible troubleshoot steps are: - Check the battery of the blood pressure machine. - Reboot the phone. Scenario 6: User has unsynced readings on blood glucose machine and app is not running. Given the application is not running And the blood glucose machine is running and has one or more unsynced blood glucose readings stored on-board And the machine and the application are paired When the application is in range of the blood glucose machine And the app collects all unsynced blood glucose data from the machine Then the application should launch And the application should provide the user with a confirmation screen that contains the most recent reading value, date and time as well as a statement that the information will be sent to the clinic, using the standard Android pop-up alert And the application should store the data in its internal database And the application should send the data to the MedlyMCC server And the application should update the Last Updated date for blood glucose When the user dismisses the popup And the application should take the user to the Main Page

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Appendix H – Summary of Alerts Algorithms The alerts algorithms for the CHF, COPD, DM and HTN were plotted according to parameters and severity. The alert messages were color-coded based on a hierarchy of severity. Those that were red and yellow would result in an alert message being sent to the clinician. Blue and green coded messages were messages for patients only because they indicated that parameters and overall status based on algorithm is normal (blue) or mild (green). CHF Alerts

COPD Alerts

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HTN and DM Alerts

The content of the messages and the hierarchy of alerts should to be explored further for future iterations of the MCC App.

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Appendix I – Verification Test

Following is a verification test protocol that was written and a sample of a verification test that

was conducted for the MCC smartphone application in order to check whether the features that

had been programmed were functioning as required.

Verification

Test Identifier

Application Section/Related Feature

Test Steps Expected Result Actual Result Pass (P)/ Fail (F)/

Incomplete (I)

Notes

14119_01 Disease specific parameters

Precondition: MCC is connected to a Dashboard patient who has CHF and Hypertension.

See #14234 and 14673

Launch app BP, Weight and Symptoms are displayed

Dashboard credentials are not working that allow transfer of this selection to the app.

F

14119_02 Disease specific

parameters Precondition: MCC is connected to a Dashboard patient who has CHF and COPD.



F


parameters Precondition: MCC is connected to a Dashboard patient who has CHF and Diabetes.

Launch app BP, BG, Weight and Symptoms are displayed


F

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Precondition: MCC is connected to a Dashboard patient who has Hypertension and COPD.

Launch app BP and Symptoms are displayed


F


parameters Precondition: MCC is connected to a Dashboard patient who has Hypertension and Diabetes

Launch app BP and BG are displayed


F


parameters Precondition: MCC is connected to a Dashboard patient who has COPD and Diabetes.

Launch app BG and Symptoms are displayed


F


parameters Precondition: MCC is connected to a Dashboard patient who has CHF, Diabetes and COPD.



F

160


Precondition: MCC is connected to a Dashboard patient who has Hypertension, Diabetes and COPD.

Launch app BP, BG and Symptoms are displayed


F


parameters Precondition: MCC is connected to a Dashboard patient who has CHF, Hypertension and COPD.



F


parameters Precondition: MCC is connected to a Dashboard patient who has CHF, Hypertension and Diabetes.



F


parameters Precondition: MCC is connected to a Dashboard patient who has CHF, Hypertension Diabetes and COPD.



F

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14188_01 First blood

pressure reading

Precondition: Blood pressure machine is paired with app, MedlyMCC is running in the background and blood pressure reading has not been taken in the last 10 minutes

Take blood pressure reading using the cuff

And the BP reading should display on the Readings page

BP displayed on Readings page

P

And the BP reading should display on the Details Page

BP displayed on Details page

P

A pop-‐up alert appears on the To-‐do page with the following message: "Your blood pressure is xxx/xx. Please take your second blood pressure reading.”

1st BP displayed on To-‐Do card and the message to take a second reading also displayed on the card.

P

14188_02 Second blood

pressure reading

Precondition: Blood pressure machine is paired with app, blood pressure reading has been taken at time 0 min

Take blood pressure reading using the cuff at 9 min


BP displayed on Readings page

P


BP displayed on Details page

P

A pop-‐upon To-‐Do appears with the following message: “Your blood pressure reading is xxx/xx. ” And the associated instructions/alert message based on the reading

2nd BP reading appears on the same page as 1st reading, as per our previous design.

P Instructions are not being tested at this point. Only the transfer of reading is being tested.

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Press OK to dismiss popup

The pop-‐up card will animate away from the screen

Card animates away on To-‐do page

P

14188_03 Second blood

pressure reading not taken in time

Precondition: Blood pressure machine is paired with app, blood pressure reading was taken and transferred to the app at 0 min

Take a reading after 11 min

A popup appears with the following message: "Your blood pressure summary has been updated. Overall you are <status>" Popup contains either of two options: Next / Okay I understand etc.

2nd BP reading appears on the same page as 1st reading, as per our previous design.

P

14188_04 Transferring

unsynced readings

Precondition: Blood pressure machine is not paired with device and contains unsynced blood pressure readings. Last reading taken was the second of a pair of readings.

Pair device with blood pressure machine


P


P

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Blood Pressure algorithm runs in the background A pop-‐up alert appears on To-‐do page with the following message for the most recent reading value taken: “Your blood pressure is xxx/xx. Overall today: <status>. <alert_status>”

1st reading and 2nd reading that were taken when the cuff was unpaired with the phone, did appear on the To-‐Do Card after pairing and initiating a 3rd BP reading. But the 3rd BP reading did not appear on a separate To-‐Do card as it should.

F

Tap OK to dismiss popup

Popup is dismissed and blood pressure summary page is displayed

P

14188_05 Taking blood

pressure reading when screen is off

Precondition: Blood pressure machine is paired with device, first bp reading of pair is ready to be taken and MedlyMCC is running in the background and screen is off

Take blood pressure reading using the cuff


P

Turn screen on, unlock if necessary


P

App opens to foreground to the page it was previously on A pop-‐up alert appears with the following message:

P

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"Your blood pressure is xxx/xx. Please take your second blood pressure reading."

Tap OK Popup is dismissed

P

14189_01 BG readings

transfer automatically to the phone when paired after a reading is taken

Precondition: 1) Phone is saved and connected with bluglu via Bluetooth 2) bluglu is connected to glucometer 3) MedlyMCC is open

Insert strip and take BG reading

Transfer confirmation appears

Syncing animation not yet implemented.

I

Tap on To-‐Do tab, if necessary

BG reading is displayed on the To-‐Do page

BG displayed on To-‐Do card

P 3 decimals. Should be 1 decimal place only.

Tap on Readings tab

And the BG reading should display on the Readings page

BG displayed on Readings page

P

Tap on Blood Sugar card on Readings page

And the BG reading should display on the Details Page

BG displayed on Details page

P

14189_02 Bulk transfer of

BG readings Precondition: 1) Phone is paired with bluglu via Bluetooth 2) bluglu connected to glucometer 3) There are untransferred BG readings on the glucometer

Take a blood glucose reading

Then all new and untransferred BG readings should transfer to the phone

New and past BG readings transferred to the phone

P

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And a transfer confirmation should appear

This is referring to the syncing animation which is not currently implemented.

I

And the latest BG reading should display on the To-‐Do page at the same time

Only the latest BG reading is displayed on the To-‐Do card. **First two tries, latest reading was not displayed on To-‐Do card. On third try, latest reading did appear on To-‐Do card

F Need to confirm with the team that only the latest reading appears on the To-‐Do page?

And the previously untransferred readings are subsequently stacked beneath the latest

Previously untransferred readings were stacked only on the third try. Readings were out of order on first two tries.

F

Tap OK button

And the most current reading should be displayed on the Readings page

Latest BG reading displayed on Readings page

P

And the new and untransferred BG readings should display on the Details page at the same time

New and past BG readings displayed in the Details page

P

14189_03 Sync with the

glucometer via Bluetooth when it is out of range

Precondition: 1) Phone is paired with the BluGlu but not connected because distance is too large and phone cannot

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(and comes in-‐range) when the application is launched -‐ phone pairs with bluglu

find the BluGlu ("Saved and Not Connected" in Bluetooth configuration menu). 2) bluglu connected to glucometer 3) There are untransferred BG readings on the glucometer The phone will continue checking whether the BluGlu is in range for 30 seconds

There is no indication

Phone does not indicate BluGlu is trying to connect.

P

Phone pairs with bluglu when it is within range

Then the phone and BluGlu will reconnect (no indication)

Phone reconnected with BluGlu

P

Tap sync button

All readings will be transferred

Sync button not implemented yet

I

14189_04 Sync with

glucometer via Bluetooth and there is an error -‐ User taps okay

Precondition: 1) Phone is paired with the BluGlu 2) bluglu NOT connected to glucometer

Taps sync button

A pop up with a sync error message should be displayed


I

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Tap "okay" in sync error message

The application will display troubleshooting steps Possible troubleshoot steps are: -‐ Check that bluglu is connected to the meter -‐ Check the battery of bluglu and the meter -‐ Check that the phone is paired with bluglu


I

14189_05 BT turned off

and the user launches the application -‐ User taps allow

Precondition: 1) Bluetooth is turned off

Launch application

Pop-‐up displayed asking for permission to turn on Bluetooth

"Bluetooth permission request" An application on your device is requesting permission to turn on Bluetooth and make your device visible to other devices. Allow?" is displayed.

F Pop-‐up displayed after navigating to "Bluetooth configuration" through action overflow.

Tap "allow" Phone turns on Bluetooth User stays on current page

Bluetooth is turned on. App transfers to screen showing devices that are connected/not connected.

P

14189_06 BT turned off

and the user Precondition: 1) Bluetooth is turned off

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launches the application -‐ User taps deny

Launch application

Pop-‐up displayed asking for permission to turn on Bluetooth

"Bluetooth permission request" An application on your device is requesting permission to turn on Bluetooth and make your device visible to other devices. Allow?" is displayed.

F Pop-‐up displayed after navigating to "Bluetooth configuration" through action overflow.

Tap "deny" Phone does not change Bluetooth settings User stays on the current page

Bluetooth is not turned on. Further messaging provided.

P

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