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You Are Here: The Pioneer Days of the Relationship Between Healthcare and Data
A SurveyGizmo Resourcewww.surveygizmo.com
A deep look into recent industry shifts and how key stakeholders are adapting
CONTENTS
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Introduction……………………………………………….............................................................p.2
Benefits of Data in Healthcare…………………………………………............................….p.3
Top Challenges of Using Data as a Healthcare Business Intelligence Tool...p.4
Data Silos…………......................……..............……..............…….....................................p.5
Data Overload……......................……..............……..............……...................................p.6
Skill Gap and Lack of Training……......................……................................................p.6
Lagging Culture Adoption……......................…….......................................................p.7
Value-Based Care as a Leading Driver………………………………………..........……….p.8
The State of Data Use in Healthcare…………………....................................................p.9
Imbalanced Priorities……………........................................................................................p.10
Data Literacy Matures Overtime…………….................................................................p.11
Innovator Spotlight: clexia™............................................................................................p.13
SurveyGizmo Use Cases......................................................p.14
Bring Data to Life with Dashboards……….....................p.15
Best Practices in Data Visualization….......................….p.16
Success Tips for Data Use and Integration….......…....p.19
About TreeHive Strategy…………........................………….p.20
About SurveyGizmo……………….....................................….p.20
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Donald Farmer, Principal, TreeHive Strategy
As the Principal of TreeHive Strategy, Donald is an internationally respected thinker in the fields of data analysis and innovation, with
over 30 years of deeply practical experience. His background is very diverse, having applied data analysis techniques in scenarios ranging from fish-farming to archaeology to advanced manufacturing. He has worked in award-winning startups in the UK and Iceland, and spent 15 years at Microsoft and at Qlik leading teams designing and developing new enterprise capabilities in data integration, data mining, self-service analytics and visualization.
Donald is an advisor to globally diverse academic boards, government agencies and investment funds on data and innovation strategy. He also advises several startups worldwide, developing products and services ranging from restaurant management software in the Philippines to intelligent supply-chain automation in Silicon Valley. He mentors individuals from junior inside sales reps to globally-focussed executives.
Donald lives with his wife, Alison, an artist, in an experimental woodland house in Seattle.
WITH INSIGHTS FROM
• From a fee-for-service payment model to a value-based care model
• Handwritten patient records have been replaced with electronic health records
• In-person care to mobile health and telemedicine
• Patients are no longer reliant on physicians to participate in their care
• Wearable technologies such as Fitbits and other health trackers are replacing large, expensive and inaccessible machines
• Personalized medicine is a patient expectation over solely providing standard procedures 1
1Live webinar hosted by Health IT Analytics. Marie Newton, Analyst at Looker and Martin Luttgersheiden, Lead Data Scientist at Healthify presented. October 11, 2017. Accessed: https://healthitanalytics.com/resources/webcasts/analytic-strategies-to-keep-up-with-modern-healthcare
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Nearly 30% of the entire world’s stored data is generated in the healthcare industry.
One patient generates some 80 megabytes of data (imaging and electronic medical record) per year.
New value pathways that this data could create are estimated by McKinsey to be worth over $300 billion in annual cost reduction.
- NEJM Catalyst
Benefits of Data in Healthcare
The healthcare industry has experienced extreme growth and maturity over the last decade. This growth has resulted in major
changes, according to Analyst Marie Newton of Looker:
We are on the heels of an industry evolution
“You need to be partnership- and collaboration-minded today to leverage relationships with others. It’s essential” says Marin General Hospital CEO Lee Domanico.
The work and communication between payors, providers, and patients demands creative and unprecedented collaboration. To be effective in this modern healthcare landscape, all stakeholders should be proactive in overcoming the hurdles that are inherent to any shift of this magnitude.
This resource’s objective is to highlight the very real challenges and subsequent frustrations felt in the healthcare industry with the transformation of data as a business intelligence tool. While there currently is a lack of a universal overhaul around the use of data in the industry, there are inroads that can be made by utilizing lessons learned from other industries that have faced this very same change.
Data can unlock a new era of healthcare, but it’s safe to say, it’s not a success to be achieved overnight. Yet, for those who are willing to shake up the industry norm, data is the answer to foster effective innovation as a whole and a pathway to an entirely new age of healthcare.
Clinician Benefits
• Improving the patient experience• Concise prevention and prediction • Benchmarking• Driving innovation• Increasing efficiency • Create targeted quality improvement programs
Administrative Benefits
• Reducing medical and operating costs• Reducing regulatory and compliance risk • Collaborating with providers• Increasing profitability and grow revenue • Streamline data sharing process• Pinpoint areas of high costs or unexpectedly low outcomes
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Yet, in practice, using data to drive decisions is a common frustration shared across the industry. The flow of unstructured patient data is being kinked at
multiple touch points of the patient journey, delaying the many known benefits. From telecommunications and finance to retail and agriculture, big data has big benefits – and healthcare is behind on capitalizing on them.
With the healthcare landscape being vastly complex, the traditional roles of healthcare professionals are shifting so quickly it’s hard to keep pace in an industry that traditionally sets the pace of innovation.
While the use of data various from industry-to-industry, the healthcare industry can holistically benefit from leveraging data in many areas, including:
In theory, data can drive decisions in every facet of healthcare from hospital boardrooms to the examination table and beyond.
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Top Challenges of Using Data as a Healthcare Business Intelligence Tool
Data Silos
“Closing Data Silos” was predicted as a 2017 trend by analytic solution provider Intellimed. According to Gene Koch, Intellimed’s Chief Operating Officer, healthcare data is often disparately found in silos that exist in:
• Strategic planning
• Market development
• Service line management
• Claims data
• Clinical data including data from Electronic Health Records (EHR)
“Healthcare systems are large entities with layers of cultural norms and systems,” says Koch. “Change does happen, but only with focused and dedicated effort.”
There is no debate about the existence of a data bottleneck between sharing patient data despite the benefits of patient care improvements and smarter business decision making. Aside from an industry-wide lack of executive commitment, data sharing barriers come with real challenges such as privacy, competition, workflow, and culture – parts of the equation that need a streamlined effort in order for data to be interoperable.
Breaking down those silos is dependent on the effort the organization is willing to put forth. From culture shifts and investment to personnel training and collaboration, it’s not the effort of a few that are going to overcome this challenge.
Data Overload
From insurance claims, clinician notes, lab results, and patient-generated data, clinicians often feel overwhelmed and not properly sourced with the required data skill set or the business
intelligence technology to accurately base potentially life changing decisions from.
A recent survey found that over 90 percent of physicians are overwhelmed by useless data. To add to the mix, distinguishing between patient generated data (from smartphones and tablets) and data that is deemed interoperable – or the ability of different information technology systems and software applications to communicate, exchange data and use the exchanged information – compiles to the list of frustrations.
“Everyone caring for patients is inundated with data,” says James R. Duncan in Diagnosis, the Official Journal of the Society to Improve Diagnosis in Medicine (SIDM). “Our senses are overwhelmed by data emanating from bedside alarms, phone calls, diagnostic images and endless pages of electronic medical records. To date little has been done to organize this torrent into a structured flow that caregivers can quickly grasp and follow over time with economy of effort. Other complex businesses are far more capable of transforming mountains of data into the nuggets of information. Medicine needs to catch up.” 2
Skill Gap and Lack of Training
In a 2017 Deloitte study, the firm found that the top three barriers to implementing and integrating analytics today include data quality, tools and technology, and access to skilled resources.
Despite the different ways data is used in the clinical and administrative/business settings in the healthcare industry, their challenges are similar.
At the core, the same challenge is paramount: there is a dire need to have in-house analytics experts or teams of experts to assist in the translation of data to inform action.
Combining the skills of analysts, healthcare professionals, and software engineers is no easy feat. Despite the evident talent acquisition challenges, the talent pool is being expected to obtain the skills of examining dense data, making it scalable, and then putting it to use.
Currently, there is limited training on this comprehensive combination of roles – it’s all taught and practices in separate disciplines. And asking clinicians to add to data science skills to their wheelhouse has its own plethora of associated challenges.
2 Duncan, James R. “Information Overload: When Less is More in Medical Imaging.” Diagnosis -- Official Journal of the Society to Improve Diagnosis in Medicine (SIDM). Published Online: June 15, 2017. Accessed: https://www.degruyter.com/view/j/dx.2017.4.issue-3/dx-2017-0008/dx-2017-0008.xml
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Lagging Culture Adoption
With the integration of new strategies backed by disruptive technology and methods, a new universal mindset industry-wide should follow. Without a
cultural consensus, adoption of data in healthcare and other technologies will lack – in turn, compromising its potential life and cost savings impact.
“...many health system executives struggle with reconciling innovation with the downsides of abandoning existing business models and disrupting long-standing culture and workflows,” says Jaan Sidorov of the Health Affairs blog.
Between governance and regulation challenges to adopting an entirely new way of working day-to-day from all sides of the industry, the hurdles to overcome are laborious and no doubt onerous; however, moving on from the business-as-usual and status-quo mindset is the only way forward for innovation to be successful.
“One reason for the slow pace of innovation in U.S. health care may be the unconscious biases that have been described in behavioral economics,” says Sidorov. “As innovators work with understandable reluctant executives and boards, it’s wise not to only describe a compelling business and clinical case, but to be prepared to address the mental errors that can otherwise undermine a good idea. It’s not about manipulating the audience with spin, but consciously elevating unspoken concerns and explicitly and honestly addressing them.”
Building and fostering a new culture – one that aligns with your business strategy, consumer expectations, technological innovations, and ideal market position -- that sticks can often be seen by executives and board members as a
“mushy” or “fuzzy” concept, especially for the healthcare industry where culture is often competing among other more tangible aspects of the business such as revenue numbers and lives saved or lost.
Yet, it’s proven in other industries that when culture adjusts, people follow suit. If innovation or data-driven methodologies are baked into the culture’s core and the organization’s leaders step up to the accountabilities of the culture, the culture is more likely to conform. In the case of healthcare, a culture shift could ultimately mean saving lives, dollars, and improving the quality of care.
Making a culture sticky can be spearheaded by the following tips from HR leader Norm Sabapathy, Executive Vice President of People at commercial real estate firm Cadillac Fairview:
1. Define a set of desired values and behaviors.
2. Align culture with strategy and processes.
3. Connect culture and accountability.
4. Have visible proponents.
5. Define the non-negotiables.
6. Align your culture with your brand.
7. Measure it.
8. Invest now.
9. Be bold and lead.
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- Navigating Value-Based Care With Data Science, Mercer (2015)
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TRIPLE AIM
As defined by the Institute of Healthcare Improvement :
“The term ‘Triple Aim’ refers to the simultaneous pursuit of improving the patient experience of care, improving the health of populations, and reducing the per capita cost of health care. Note that the Triple Aim is a single aim with
three dimensions.”
Value-Based Care is a Leading Driver for the Use of Data in American Health Systems
Success with value-based care hinges on the ability to access data-driven insights.
“Value-based care represents a fundamental shift in how health care delivery is organized, paid for and received,” according to global consulting firm Mercer. ”If it is structured and deployed successfully, it can reduce healthcare costs, increase the quality of care and improve the patient experience, thus achieving the triple aim.”
• Instead of paying providers for each service they provide, with value-based care models, providers are compensated based on results.
• Provider results are measured on cost, quality, and patient experience.
The industry shift towards a value-based payment model supported by data insights can be best explained with statistics:
• 86% of mistakes made in healthcare are considered administrative, the Journal of Healthcare Information Management (JHIM) found.
• The Journal of Patient Safety estimates these errors contribute to the loss of some 400,000 lives per year.
• 28% of ICU autopsies reported at least one misdiagnoses, a review of autopsy studies found.
• Up to 30% of current healthcare spending is wasted, a research team at the Dartmouth Institute for Health Policy and Clinical Practice found, a figure that the New England Institute of Health, McKinsey, and Thomson Reuters confirmed.
• Patient information is lost 30% of time due to being paper-based, isolated, and disconnected between providers,
according to the Technology CEO Council.
• Centers for Medicare and Medicaid Services (CMS) research found that nearly one out of every five Medicare patients ends up back at the hospital in less than one month after being discharged
– resulting in two million readmissions per year – a leading indicator of poor quality care. Experts estimate these high readmission rates is costing Medicare around $26 billion annually, $17 billion of which could be potentially avoidable.
The adoption of a value-based model is . However, Mercer points out that many health systems are already participating in this model
– but some may not even realize it yet.
Since most major insurance companies operate under a value-based agreement, it would behoove healthcare employers to capitalize on the benefits of the model since they are likely currently paying for it. Taking advantage of value-based benefits begins with implementing a data-first mindset and practice.
Knowing the intricacies of using data as part of the business strategy can help smooth the transition into the value-based model and should make a strong business case for organization’s to invest in the necessary resources.
While data is being viewed as a higher priority in healthcare than ever before, recent Deloitte research suggests the focus is not yet sufficient.
There needs to be a collective effort on building and maintaining an effective analytic collaboration approach to unlock the mutually beneficial relationship potential between each stakeholder involved.
Taking a broad national approach to health care is no longer sufficient. Health care is practiced locally, and so solutions must be local as well. Value-based care holds great potential, but only if employers have the vital information they need to make the right decisions.
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Data is being analyzed and utilized in silos, not collaboratively.
Health plans
Use claims and enrollment data to identify high-cost populations and care inefficiencies at a macro level.
Analysts
Focus on native proprietary data sets.
Health systems
Rely on clinical data to deliver patient—centered care.
The State of Data Use in Healthcare
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Priorities are Imbalanced
Doctors have an average of 12 minutes with a patient, Arlen Meyers, MD, MBA, President and CEO of the Society of Physician
Entrepreneurs and professor emeritus of otolaryngology, dentistry, and engineering at the University of Colorado School of Medicine told us. And as such, priorities are challenged.
When it comes to using patient data that is channeled in from insurance companies, medical records, and patient-derived data, healthcare professionals are found standing in front of a patient between a rock and a hard space.
There are many variables that feed into this frustration – from a lack of universal data collection methods and storage protocol, to skill and training to read, understand, and take action on patient data sets.
While there is a dire need for overarching reform in this area, there is low hanging fruit to pick that will facilitate the utilization of data sets to trigger data-driven decision making in the doctor’s office more a feasible reality.
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Data Literacy Matures Over Time
“…analogously, data literacy emerges not merely as an individual ability,” says Donald Farmer, Principal at Seattle-based TreeHive Strategy. “It grows in business as a practice of organizations, transmuting teams, firms and economies.”
For any overhaul of magnitude to occur, it takes two fundamental variables: time and effort.
For example, the evolution of one core data source for patient information, the electronic health record (EHR), has been a work in progress for more than 50 years. Relatively speaking, we’re pacing pretty well when it comes to making a big data revolution in healthcare a reality.
Excerpted from Deloitte’s findings from their 2017 US health plan analytics survey.
Source: https://www2.deloitte.com/us/en/pages/life-sciences-and-health-care/articles/us-health-plan-analytics-survey.html
A well-developed analytics capability is a basic business necessity
More than 75 percent of survey respondents expect their analytics spending to increase in the next year, the Deloitte Center for Health Solutions 2017 US Health Plan Analytics Survey found.
The years following indicate a similar trend.
If the spend is predicted, the associated skills and aptitudes need to align accordingly. There is not much room in the current and future high-tech data-supported landscape for laggards or late adopters.
Hospital and health systems are in no doubt changing their way of operating from both a business perspective and a care perspective to correlate with data science methodologies. To not just succeed, but to thrive in the future landscape of modern data-driven healthcare, the Society for International Strategy and Market Development of the American Hospital Association states the industry as whole needs to obtain the following:
To start working toward overcoming the complex challenges ahead, the same organization implies that today’s healthcare leaders need to foster:
• Creative partnerships, that will increasingly evolve into more fully integrated arrangements (i.e. data science and analyst consultants)
• Affiliations with traditional and non-traditional providers (i.e. technology and software vendors)
• A broad range of convenient patient access points
• Online patient links to scheduling, clinicians, health records, etc.
• A patient experience that recognizes socioeconomic and ethnic factors
• Programs that manage the care of defined populations
• Well planned services across the care continuum in strategic locations
• Comprehensive intelligence to inform clinical and financial decisions
• Effective value-based payment arrangements
• Skills to manage risk-based payments
• Innovations that improve care and provide new revenue streams3
3Futurescan: Healthcare Trends and Implications 2017-2020. “The Building Blocks of Transformation.” Society for Healthcare Strategy and Market Development American College of Healthcare Executives American Hospital Association. http://trustees.aha.org/envtrends/Futurescan%20PPT%20
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The data that is submitted into the app from the patient is then displayed to the doctor in way they can quickly interpret before adjusting treatment while maintaining the integrity and quality of the data. The data collected from the patient is fed directly into their EHR, leveraging a more efficient alternative to manually entering sensitive and private patient information.
Not only does cliexa display one innovative way of how patients and doctors are communicating outside of the examination room, it showcases how caregivers stay updated in real-time about a patient’s condition.
How cliexa™ helps clinicians to make data-backed decisions:
For patients:
• Tracks symptoms, medication data, and complication data and easily share with a care team
For care providers:
• Enables providers with the time and ability to deliver value-based care
For payors:
• Access to improved outcomes, chronic care analytics, and streamlines processes
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Not Minding the Gap, But Filling It – Innovator Spotlight
cliexa™
While the industry is waiting for steps to be taken to develop an overarching solution from a policy and legislation perspective, independently produced solutions are coming to surface.
Currently, the app has over 5,000 active users as of October 2017, the company’s Founder and Chief Executive Officer Mehmet Kazgan told us.
Use Cases from SurveyGizmo Clients
We often ask our clients how they use our data platform as part of our continuous product feedback loop. Results bucketed healthcare use cases into three major buckets.
Internal Benchmarking
Using the data collected from patients in follow-up communication such as a survey
or questionnaire, doctors are benchmarked against other doctors. The data collected on each caregiver provides transparent insights
into bedside manner, proper discharge instructions, and communicating the surgical process. By displaying these benchmarks on highly visible and easy-to-read dashboards,
creates a friendly competition amongst staff and keeps care improvement top-of-mind. Additionally, these statistics feed into the
physician’s HR record.
Patient Satisfaction
Similar to a standard one-question Net Promoter Score (NPS), some clients are
creating a dashboard to be displayed on a computer monitor in the office that shares
the current satisfaction rate of patients based on data from feedback surveys,
questionnaires, and follow-up calls.
Community Health
For a community in Niger, one non-profit tackles the region’s challenge of distributing
female contraception to remote villages using the population’s datasets compiled from
surveys. A data-first approach to this issue has helped the non-profit control supply and
demand of various contraception types and to reach the people who need it the most.
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Bring Data to Life with Dashboards
We’ve addressed the complexity of analyzing data, and how the healthcare industry is struggling to find, invest, and foster the skills needed to do this kind of advanced work. One way to address the issue – albeit perhaps temporary – is to build a basic dashboard using the tools you already have.
Starting out with visualizing data as a healthcare professional with no data science training or background, it’s best to start simple.
”Don’t be intimidated by the thought of creating a visual version of data,” Penny Cooper, Decision Support Manager at Augusta Health told Health IT Analytics. “Our infection rate dashboard was very easy to create. We started the project in Microsoft Access, because it had all the elements we needed to put something together.”
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losing Data Silos” was predicted as a 2017 trend b
By Donald Farmer, Principal, TreeHive Strategy
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Best Practices in Data Visualization
If you are looking to improve your data visualization techniques, the internet is full of advice for you. Never use pie charts! Avoid 3D effects! Use this advanced chart type or that new chart type ... it can be quite intimidating, especially as people often hold very strong opinions.
Fortunately, there are a few simple principles which can guide you towards your own best practices.
Know your audience
Information design isn’t about the science of data, it’s about people. You share visualizations in order to give useful information to others. So, it’s important to understand their needs, skills and interests.
Is your audience data literate? Will they readily understand the charts you are showing them? Some chart types may need some explaining – for example, I still have to think twice when looking at a bullet chart.
The more you know about your users and their understanding of data, the better. You’ll be able to craft visualizations that work for them simply.
Focus on your purpose
When planning your visualization have its purpose clearly in your mind. What is the visualization for? At the stage, don’t worry about the information you will show, but ask yourself: what decisions will be made, using this visualization?
After all, if the visualization will not help with some decision, why are you building it? Hopefully not just for decoration.
A good visualization provokes conversations and discussion about the topic; it doesn’t just answer questions, it raises questions too.
What do you want to show?
Once you know your audience and have a good idea of the purpose of your visualization, it’s time to get down to choosing your chart types. What do you want to show?
Comparison
If you want readers to compare values bar charts of various kinds are very useful. You can easily compare between items.
Change Over Time
If you are showing change over many time periods - more than just a few data points - then a line graph is most useful. Also lines make it easy to plot multiple series together.
However, if you are showing change over just a few values - says changes over the last six months - consider using a bar chart again, unless you have multiple series.
Composition
This means showing how a single value (sales, perhaps) is made up of other values (say, for each region.)
The pie chart is a notorious example of a composition visualization. It has a bad reputation because so many pie charts are badly used. It probably is best to avoid them unless you have a good reason. Certainly they are easy to understand, so long as they only have a very few values, and so long as you don’t want people to make exact comparisons at a glance.
Relationship
To show how two or more values are related (for example, age and educational level) consider using a scatter plot to show both in a simple way. Each data can be shown as a point or bubble positioned as an x,y co-ordinate representing the two values.
Some scatter plots also allow you to change the size of the bubbles to show another value, such as income.
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losing Data Silos” was predicted as a 2017 trend b
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Colors and Aesthetics
Choose colors carefully to convey information. It’s a good practice to use one color for consistency throughout your document, web page or presentation. Introduce new colors when you want to make comparisons or show contrasts in a single visualization.
You can use shades of the same color to convey information. Shaded maps are popular, but shaded charts can be very effective too. Note that it can be difficult to make exact readings of a shade, so don’t rely on shading for precise interpretation
Multiple colors, as I said, can show contrasts. But too many colors is confusing and almost literally sore on the eyes. If you are thinking of using more than 10 colors, think carefully. If you plan on using 20 - think again!
A Final Word
The most important best practice I can recommend is also the most overlooked. Test your work!
It’s a really good idea to sit down with a typical user of your work. See what they like and don’t like. Ask them to explain to you what conclusions they can draw from your visualization. What questions does it raise? What questions does it answer? What conversations do you have when discussing the chart?
Perhaps make two or three versions of your visualization to try out different techniques. See what works best in practice by asking users.
As you get confident with your design, you’ll increasingly know what works well, but it’s good not to become complacent. Remember that visualizations are not just about information - like all work, our focus needs to be on people and their needs.
losing Data Silos” was predicted as a 2017 trend b
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Success Tips for Data Use and Integration
• Scalability. The sheer amount of business problems that regularly exist in healthcare organizations make it challenging to address everything all at once. Narrowing in on specific problems, that if corrected, bring the most value should be a high priority and demand focus.
• Standards. To see business improvements quarter over quarter, benchmarking and performance reports set the stage of where to improve, provides an efficient return, and supplies ample insights to apply to the overall business strategy.
• Self-Service. Filter large data sets to share the narrative of only the past two to three years while archiving older information. This segmentation of the data will allow for quicker recall and increased use of data by clinicians and administrators and provide focus on the most pressing issue(s).
• Governance. Data can be sliced and diced in many different ways to tell many different stories. Varying definitions and understandings of healthcare data can negatively impact the use of the data and lead to privacy concerns and security breaches. Standardize definitions of metrics and data throughout the organization before drawing insights from it to ensure the organization is working from the same page.
• Take it one step at a time. The path to becoming a data-driven organization that works off insights only starts to become reality if you take the first step. If you’re looking to become more efficient in your business, save money, and offer personalized and local care, consider these initial priorities from Deloitte:
1. Get leadership buy-in and commitment.
2. Determine and set priorities and goals for analytics for both the administrative side and the clinical side.
3. Align the business’s strategy with the data strategy to maximize their mutually beneficial relationship.
4. Set a quality framework for any and all data to ensure it’s use and credibility in decision-making.
About TreeHive Strategy
At TreeHive, we advise software vendors, investors, and enterprise customers with unique strategic guidance. We have practices our craft through many creative years in the software business, working at all stages from startups to world-leading, complex projects. We specialize in analytics and data technologies but our experience in designing and creating software products and services is wide-ranging and distinct.
Clients value our perspective and innovative thinking. We value their trust and openness to radical ideas. Our relationships are founded on insight and empathy as much as on technical excellence and know-how.
About SurveyGizmo
Founded in 2006, SurveyGizmo is a powerful survey and data insights platform that empowers business professionals to make informed decisions. Through high-powered application software, it offers user-friendly data collection tools for understanding your customers, markets, and employees in real time and communicating this information across an organization. It provides data insights in over 205 countries, with 50,000 new surveys created and 7.5 million responses every week for customers like Fedex, Microsoft, Bloomberg Television, and GE.
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