1304023 a systematic review for palliative care clinical indicators for...

A systematic review for palliative care clinical indicators for pain

Final report

This report was prepared for the Department of Health by:

Pain & Palliative Care Department

Peter MacCallum Cancer Centre

St Andrews Place

East Melbourne Victoria

Locked Bag 1 A’Beckett Street

Victoria 8006 Australia

Phone +61 3 9656 1111

www.petermac.org

Authors: Alex Brando and Odette Spruyt

If you would like to receive this publication in an accessible format please phone

03 9096 2085 using the National Relay Service 13 36 77 if required.

This document is available as a PDF on the internet at <www.health.vic.gov.au/palliativecare/>.

© Copyright, State of Victoria, Department of Health 2013

This publication is copyright, no part may be reproduced by any process except in accordance

with the provisions of the Copyright Act 1968.

Authorised and published by the Victorian Government, 50 Lonsdale St, Melbourne.

Except where otherwise indicated, the images in this publication show models and illustrative

settings only, and do not necessarily depict actual services, facilities or recipients of services.

May 2013 (1304023)

A systematic review for palliative care clinical indicators for pain

Final report

Acknowledgements

The Systematic Review of Palliative Care Clinical Indicators for Pain project was funded by the

Victorian Department of Health to support the work of the Palliative Care Clinical Network.

The project team acknowledges the assistance of CareSearch in conducting the literature review.

We also thank UltraFeedback for their pro bono support in developing and hosting the web survey.

The project team would like to express its appreciation to the project advisory committee for their

guidance and support.

The project team is also grateful to those who contributed greatly to this project by participating in

interviews and the online survey. Successful completion of this project would not be possible without

their kind support.

Executive summary 1

Introduction 3

Background 3

Project objectives 3

Project scope 3

1. Methodology 5

1.1 Literature review 5

1.2 Expert panel 6

1.2.1 Round 1 – appropriateness voting 6

1.2.2 Round 2 – necessity voting 6

1.2.3 Result validating 7

1.3 In-depth interview and survey 7

1.3.1 Survey design 7

1.3.2 Data analysis 8

2. Results and discussion 10

2.1 Literature review result 10

2.2 Expert panel result 12

2.2.1 Outcomes from round 1 – appropriateness 12

Outcomes from round 2 – necessity 15

2.2.2 Validating voting results 16

2.2.3 Result and discussion 17

2.3 Survey result 17

2.3.1 Respondent profi le 17

2.3.2 Tools and quality improvement initiatives in use 20

2.3.3 Data entry 20

2.3.4 Top benefi ts and barriers 21

2.3.5 Cluster analysis result 22

3. Recommendations 31

3.1 General recommendations 31

3.1.1 Minimum requirement 31

3.1.2 Individual organisation 31

3.1.3 Statewide implementation 35

Contents

3.2 Recommended solutions to barriers 38

3.2.1 General resource issues 38

3.2.2 Lack of IT support 38

3.2.3 Low awareness within an organisation 38

3.2.4. Leads to extra work for staff 39

3.2.5 Lack of ongoing funding to support data entry 39

3.2.6 Lack of staff with the appropriate skills 39

3.2.7 Lack of support from staff 40

3.2.8 Lack of support from management 40

3.2.9 Low priority within our organisation 40

3.2.10 Not related to patient care 40

3.3 Suggestions for services within each group characterised in the survey 40

3.3.1 General suggestions 40

3.3.2 The enthusiast group 41

3.3.3 The conservative group 42

3.3.4 The cautious group 42

Appendix 1: Databases searched 44

Appendix 2: Terms used for literature search and results 45

Table A1: Search strategy applied to all databases 45

Table A2: The PubMed search strategy incorporating the CareSearch palliative care fi lter 45

Appendix 3: Candidate indicators for expert panel 46

Appendix 4: Survey content 68

Appendix 5: Data specifi cation for clinical indicators for pain 70

Defi nitions and benchmarks of recommended indicators 70

Data elements required for each indicator 73

Data elements defi nition 74

References 75

v

Table 1: List of agreed indicators from round 1 12

Table 2: List of changes to indicators from round 1 13

Table 3: List of indicators complied with the relaxed rule from round 1 13

Table 4: List of highly discordant indicators from round 1 14

Table 5: List of indeterminate indicators from round 1 14

Table 6: List of agreed indicators from round 2 15

Table 7: List of changes to indicators from round 2 15

Table 8: List of indicators complied with the relaxed rule from round 2 16

Table 9: Discipline 20

Table 10: Top three benefi ts and barriers 21

Table 11: Group vs service type 24

Table 12: Group vs region 25

Table 13: Group vs service delivery areas 26

Table 14: Group vs staff number 27

Table 15: Group vs usage time of quality improvement projects 28

Table 16: Group vs usage time of LCP 29

Table 17: Group vs usage time of assessment tools 30

Table 18: Indicative coordination time for the three phases 34

Table 19: Breakdown of indicative time requirement 35

Table 20: Breakdown of indicative time requirement of network coordination 37

List of tables

vi

Figure 1: Indicators by type 10

Figure 2: Indicators by setting 11

Figure 3: Indicators by detail level 11

Figure 4: Service types of respondents 18

Figure 5: Service delivery areas of respondents 18

Figure 6: Health regions of respondents 19

Figure 7: Staff numbers of respondents 19

Figure 8: Tools and quality programs in use by respondents 20

Figure 9: Perception profi les of respondent groups 23

Figure 10: Perception profi les of respondent groups – radar 23

Figure 11: Distribution of groups by service type 24

Figure 12: Distribution of groups by departmental region 25

Figure 13: Service delivery areas of groups 26

Figure 14: Distribution of Groups by staff numbers 27

Figure 15: PCOC participation time in groups 28

Figure 16: LCP participation time of groups 29

Figure 17: Assessment tools using time of groups 30

Figure 18: Factors and stages of implementation for individual organisations 32

Figure 19: Stages of implementation for organisational level and network level 35

List of fi gures

1

This project is one of four initial projects undertaken on behalf of the Palliative Care Clinical Network

(PCCN) to address a key priority area of Victorian palliative care strategic directions 2011–2015

(Department of Health 2011), namely ‘Providing quality care supported by evidence’.

This project has three main objectives. The fi rst is to undertake a review of the evidence base for

clinical indicators for pain in palliative care practice. The second is to recommend a group of clinical

indicators for pain to the PCCN, for statewide implementation. The third and major part of the

project is to develop a business case for organisations to use in adopting these indicators into their

organisational operational plans.

A comprehensive literature review was conducted and an expert panel established to determine

candidate clinical indicators to recommend. An important factor to note is that a Cochrane-style

systematic review was not within the remit of this project. A survey was conducted to determine

major perceived barriers and benefi ts to implementing these indicators. Service providers’ attitudes

towards quality improvement programs were also assessed via the online survey.

The literature review used a broad search strategy provided by CareSearch. Seventy-four references

were identifi ed from several major health databases, including Medline (1950–2010) and Embase

(1980–2010). An additional 22 references were identifi ed through reference tracking. From these

references, together with guidelines and policies published by government departments and Australian

and international organisations, the researchers identifi ed 113 clinical indicators for pain, which fall into

four major categories: outcome, structure, process and symptom. This project focused on process

indicators for clinical-level quality improvement to complement and avoid duplication with national

projects such as the Palliative Care Outcomes Collaboration. From these, 29 indicators were chosen

by the project team for consideration by a seven-member expert panel with backgrounds in medical,

nursing and management, and derived mostly from the Victorian palliative care sector.

The expert panel followed a modifi ed RAND/UCLA Appropriateness Method approach to achieve a

fi nal set of indicators, rating the 29 indicators on the following criteria: appropriateness (assessing

validity, feasibility and generalisability) and necessity (in terms of being fundamental to care and

consistent with quality of care). An independent shadow rater with both a management and nursing

background validated the expert panel’s results. The resultant six indicators recommended for

implementation by the Victorian Department of Health through the PCCN were pertinent to two areas

of pain management, namely pain assessment and analgesic prescribing.

The recommended indicators are as follows:

• pain assessment indicators

– use of a validated pain scale

– assessing pain for a new patient

– regular pain assessment

• analgesic prescribing indicators

– prescribing for breakthrough pain

– scheduled pain medication for severe pain

– providing a bowel regimen with an opioid.

The online survey items were developed in conjunction with the concurrent PCCN assessment tools

project and were based on interviews with fi ve palliative care managers and the research team. The

survey included items about current use of tools and participation in quality improvement projects,

and asked about barriers, benefi ts and attitudes towards clinical tools and quality improvement

Executive summary

2

projects in use. Respondents were asked to rate their level of agreement with the questionnaire

items about specifi c barriers and benefi ts using a fi ve-point Likert scale. The survey was sent to

60 service providers, 38 of whom (63 per cent) responded. Responding services represented the

range of Victorian palliative care service providers when compared with the Palliative care service

delivery framework (SDF) (Aspex Consulting 2010). Compared with SDF, community services were

more highly represented in survey respondents while consultancy and inpatient services were less

represented. No publicly funded day hospice responded to the survey. Survey respondents’ service

delivery areas and regions are distributed similarly to the SDF mapping.

The analysis of the survey data revealed that the main benefi ts of quality improvement projects

perceived by service providers were that they enable benchmarking, demonstrate care practices and

upskill staff. The main perceived barriers were that they lead to extra work for staff, and that there is

a lack of IT support and a lack of ongoing funds to support data entry.

Three different types of services were identifi ed through cluster analysis of all perceptions

and attitudes. They were named as enthusiast, conservative and cautious according to their

characteristics. Locality, service type, service area and organisation size did not seem to have a very

strong infl uence or correlation on perceptions. There was a pattern that those groups participating in

most quality improvement projects had been using quality projects or assessment tools for a longer

time than those less actively participating.

To help Victorian palliative care service providers to implement the recommended clinical indicators,

stages are identifi ed for both individual organisations and the statewide network. For an individual

organisation, the recommended stages are: the pilot stage, the integration stage and the continuous

improvement stage. Organisational change, culture building for quality improvement, education and

communication are considered key factors throughout all stages. For the statewide network, the stages

are referred to as: the modelling stage, the expanding stage and the collective improvement stage.

Phased introduction of indicators according to site-specifi c capacity

Members of the so-called enthusiast group would be well placed to act as models for other services

in the modelling stage of statewide implementation. Organisations of the so-called conservative

group will likely be ready to participate in quality improvement implementation in the expanding stage

of implementation. Introducing validated pain tools into routine clinical care rather than undertaking

to implement the recommended indicators is considered more suitable initially for the cautious

group, with the purpose of increasing awareness and willingness to participate and graduated

introduction. A detailed process and methodology are suggested for implementation in all settings,

along with brief solutions against each barrier.

The project team recommended the following as minimum requirements to introduce the

recommended indicators:

• a validated tool for pain assessment to be adopted by each palliative care provider

• documentation of the required elements for the recommended indicators in a precise and timely

way that facilitates quality improvement

• demonstration project(s) in typical palliative care settings to establish initial benchmarks and to

showcase improvements in the quality of care for patients by implementing the recommended

indicators.

It is recommended that the PCCN facilitate and support the coordination of the demonstration

project(s) for the modelling stage of statewide implementation.

3

Background

As part of its strategic approach to addressing the goals of the national strategy, the Victorian

Department of Health allocated funding to uncover areas of defi cit of care in the Victorian palliative

care sector, and to develop strategies and identify aids that may contribute to realising the national

goals.

The Palliative Care Clinical Network (PCCN) was established by the Department of Health’s Palliative

Care team to oversee the clinical elements and implementation of:

• Strengthening palliative care: Policy and strategic directions 2011–2015 (Department of Health

2011)

• a service delivery framework and service capability framework

• the Clinical Service Improvement program.

In an evaluation of the 2004–09 palliative care policy’s implementation, there were several

recommendations about the key strategic priorities to be addressed for 2011–15. This project arises

from the recommendation ‘Establish a PCCN and a statewide program for the uptake of evidence

into clinical practice’ under strategic direction 6 of the policy ‘Quality care at all times’.

Project objectives

This project has three components. The fi rst is to undertake a review of the evidence base for clinical

indicators for pain in palliative care practice. The background review includes published guidelines

and other key documents summarising expert opinion and recommended best practice, recognising

that the evidence base for such indicators remains weak.

The second component of the project is to recommend a group of clinical indicators for pain to the

PCCN, for statewide implementation.

The third and major part of the project is to develop a business case for organisations to use in

adopting these indicators into their organisational operational plans. This component of the project

focused on how the recommended indicators will become part of the quality framework for palliative

care organisations across Victoria. The implementation of these indicators was tailored to different

levels of palliative care service delivery, in keeping with the service delivery framework and service

capability framework. Through establishing statewide clinical indicators for pain in palliative care

practice, services will be supported in delivering the highest quality care for their patients.

Project scope

The project included a review of existing literature and quality improvement projects in Australia and

internationally. The project did not include a Cochrane-style systematic review.

The project recognised the quality improvement projects currently underway in Australia, including

The National Standards Assessment Program (NSAP), Palliative Care Outcomes Collaboration

(PCOC), Australian and New Zealand Society of Palliative Medicine (ANZSPM), CareSearch and the

National Pain Summit’s Pain and Palliative Care Working Group, and will draw from and align with the

outcomes and recommendations of these projects wherever possible.

The project aimed to provide Victorian palliative care organisations with a methodology by which

the recommended indicators might be integrated into their existing quality improvement programs.

Introduction

4

It recognised that many organisations in Victoria currently participate in PCOC, NSAP and other

relevant quality improvement programs and that the recommendations of this project need to be

sensitive to and support previous commitment to quality improvement.

A business case was developed that will assist organisations to implement and evaluate the impact

of introduction of the recommended indicators into their quality improvement activities.

The project recommended to the department a frequency of reporting of data and methodology

for benchmarking pain clinical indicators, working closely with departmental data analyst for

palliative care. It also developed guideline(s) and requirement(s) to help organisations assess and

collect clinical indicator data, as well as guideline(s) and requirement(s) for developing educational

information about indicators and relative data collection tools.

The project did not include implementing or piloting the tools in any palliative care setting, nor

did it develop a database for organisations to collect the data. In recognition that the science of

implementing medical knowledge and quality improvement is in its infancy, this project did not

include research into the outcomes of implementing the recommended pain clinical indicators.

5

1.1 Literature review

A comprehensive literature review was conducted to identify current data collection and indicator use

by Australian and international services. The literature review included a review of academic literature,

including unpublished articles and conference abstracts, and grey literature, including reports and

guidelines from service providers, governments and professional associations.

CareSearch provided support for the academic literature search. A broad search strategy was

applied to several major health databases (see Appendix 1) in order to identify the evidence base for

clinical indicators of pain in palliative care. The references of identifi ed articles were also examined

and articles included where they were unique. An internet search was also executed. Articles

identifi ed were downloaded into an EndNote X3 Library for that database. After all searches were

completed, individual EndNote Libraries were merged and duplicate records were deleted.

Only the English language was applied. Only the Evidence-based Medicine (EBM) Reviews results list

was screened for relevance. This was done because search terms had worked on the full text, rather

than just title, abstract and subject fi elds, and the results were clearly not on topic. No consistent

Medical Subject Heading term (MeSH term) could be identifi ed for the topic of clinical indicators,

except within the Cumulative Index to Nursing and Allied Health Literature (CINAHL) database. A

broad and sensitive search strategy was therefore constructed using text words, truncated where

appropriate. This was applied consistently across all databases except PubMed. The PubMed

search used a variation on this search. This was required for two reasons: PubMed does not allow

proximity limiters and a more sophisticated palliative care fi lter can be applied in this database for the

palliative care component. Please refer to Appendix 2 for detailed terms used.

Identifi ed literatures were then evaluated by the project offi cer according to predefi ned procedure

and research questions. A detailed literature review protocol was developed to ensure consistent

quality of the review process. The review focused on the following questions:

What

• What are the data being collected about pain to improve quality of care?

• What methods are people using to collect data on pain and pain management?

• What are they doing with those data?

• What settings are suggested for each data element (indicator)?

Why

• Why are those elements chosen?

• What is the evidence? (literature review, expert panel decision, pilot run/trial)

• How strong is the evidence? (steps: classify, evaluate, summarise)

How

• How are the data being collected?

• How are the data reported?

• How are the data analysed?

• How are the data used to assess and improve quality of care?

Abstracts were evaluated by the project offi cer. A review of the full text was conducted where a

literature was believed to be a close fi t for the purpose of answering the above research questions.

1. Methodology

6

Some of literature was also reviewed by an independent reviewer according to a predefi ned literature

review protocol to ensure consistency.

1.2 Expert panel

A modifi ed version of RAND/UCLA Appropriateness Method (RAM) was used based on instructions

from The RAND/UCLA appropriateness method user’s manual (Fitch et al. 2001). Seven experts, the

lower limit as recommended in the manual, were engaged in the process instead of the traditional

nine, although there is no evidence showing a relationship between validity of results and the number

of experts. One cycle of appropriateness voting and one cycle of necessity voting were conducted.

Modifi cations of indicator defi nition, including numerator and denominator, were fi nalised between

two rounds of voting.

An initial list of indicators with detailed defi nition was provided before voting. The indicators and

defi nitions were determined by the project team based on a previous literature review and internal

discussion.

Panel members were not provided with the literature reviewed by the project team. Rating decisions

were expected to be made based upon the panel member’s expertise and existing knowledge of

clinical quality improvement, especially of current status in Victoria. Supporting literatures were only

provided upon request.

1.2.1 Round 1 – appropriateness voting

The list of indicators was distributed together with a rating form. The fi rst round consisted of voting

on the appropriateness of each indicator with consideration of the following factors:

• Validity: Is this indicator supported by the voter’s knowledge?

• Feasibility: Is it feasible to use this indicator in practice?

• Generalisability: Is this indicator applicable for all settings or just a few of them?

Each indicator was rated on a 1–9 scale, with 1 representing highly inappropriate and 9 highly

appropriate.

The criteria of agreement and disagreement between experts were defi ned according to The RAND/

UCLA appropriateness method user’s manual.

Defi nition of classifi cation rules:

• Strict agreement for appropriate: All seven ratings fall in the 7–9 region.

• Relaxed agreement for appropriate: Six ratings fall in the 7–9 region, one rating falls in the 4–6

region.

• Disagreement: At least one rating falls in each of two extreme regions (1–3 and 7–9).

• Indeterminate: All other scenarios not included above.

1.2.2 Round 2 – necessity voting

The result from round 1, with modifi cations based on recommendations, formed the basis for the

second round of voting. This round consisted of voting for necessity, considering the following

factors:

• Fundamental: This indicator is essential to establish quality improvement.

• Consistent quality of care: It will be hard to maintain quality of care to a good level without

implementing this indicator.

7

Each indicator was rated on a 1–9 scale, with 1 representing highly inappropriate and 9 highly

appropriate. The criteria of agreement and disagreement between experts were the same as

round 1.

1.2.3 Result validating

Since the project used a simplifi ed version of RAM, it is important to introduce a protection

mechanism to minimise possible bias. To validate the result, a shadow rater was introduced later to

go through the whole process again. Scoring results from all eight raters were examined against the

same rules.

1.3 In-depth interview and survey

A structured questionnaire was developed from in-depth interviews with fi ve targeted palliative care

providers from diverse clinical and administrative backgrounds. The questionnaire explored the

relevance of nine commonly perceived barriers and eight benefi ts. Three questions were added to

explore the respondent’s impression of the organisation’s interest and the value given to the service

provider’s efforts to implement these tools and projects. The questionnaire was set up as a web

survey and distributed online to 60 service providers across the state. Appendix 4 is a print version

of the fi nal web survey.

1.3.1 Survey design

The survey was jointly administrated by project offi cers of both projects and the survey service

provider UltraFeedback.

Survey purpose

1. To understand the current situation within Victorian palliative care service providers (including tools

in use) and participation in quality improvement projects or initiatives.

2. To identify barriers, benefi ts and attitudes towards clinical tools and quality improvement projects

in use.

3. The data will be used to form recommendations to the PCCN for implementing new tools and

clinical indicators for pain.

Target audience

The survey was designed to be responded to by one representative from each palliative care service

provider.

‘Palliative care service provider’ refers to the following:

• if the organisation is for palliative care purpose only (‘hospice’ or ‘service provider’ means the

whole organisation)

• if the organisation is multidisciplined (‘a hospital with palliative care service’ or ‘service provider’

means the palliative care department of the organisation).

Selection criteria

Participants were representatives from Victorian palliative care service provider who could best

respond to the questions in the survey, ideally the person who was in charge of quality issues or

head of the department or organisation.

8

Participant identifi cation procedures

The Department of Health provided a list with the contact details of all palliative care agencies. This

list is available publicly.

Survey delivery method

The survey was delivered in the form of online web survey. A cover letter on behalf of the Department

of Health and PCCN, plus a link to the online survey, were distributed by UltraFeedback.

The survey information was included in the weekly newsfl ash provided by Palliative Care Victoria.

Two reminder emails were sent during survey collection.

Consent process

A cover letter sent with the survey link included the following statement,

‘By fi lling out the survey you are consenting to participate.’

Privacy issues

No individual participants were identifi ed in any publication or report arising from the survey.

Ethical considerations

This survey was targeted at palliative care service providers to collect information on tools and

quality improvement initiatives they were using at the time. It did not involve any patient contact or

intervention. Data collection was anonymous. Data will be stored for seven years and confi dentiality

maintained throughout.

1.3.2 Data analysis

Methods to identify the top three benefi ts and barriers

Different methods were adopted to fi nd out the overall top three barriers and benefi ts perceived by

respondents.

Method 1 – Original scores

The average of a respondent’s scores for the same question asked about each tool/initiative was

used as this respondent’s overall score for this question against all tools and initiatives. The average

score of all respondents’ responses was used as the fi nal score for the overall answer to each

question. The top three barriers and benefi ts were selected based on these average scores.

Method 1.1 – Original scores without RUG-ADL, Karnofsky

Since Resource Utilisation Groups – Activities of Daily Living (RUG-ADL) and Karnofsky scores are

part of PCOC data collection, this method removed ratings for both and used the same calculation

as in method 1 to choose the top three options.

Method 1.2 – Original scores for PCOC only

Because of the high similarity between PCOC and this project, especially when compared with the

rest of the available options, it is reasonable to use PCOC to identify potential barriers and benefi ts

for implementing clinical indicators for pain.

Method 1.3 – Original scores for PCOC and LCP

Liverpool Care Pathway (LCP) ranking is not analysable due to limited responses. Combined results

of PCOC and LCP will give an overall ranking for quality improvement projects only.

9

Method 2 – Weighted ranking

It is possible that using methods 1–1.3 will generate results with the same scores. In this case, it will

not be possible to distinguish between options. Another problem is one particular question may only

have one response with a very high score, which will reduce the credibility of the fi nal results.

To minimise the infl uence of these problems, the top three benefi ts and barriers were identifi ed for

each clinical tool or quality project, and they were given rank scores of 3, 2 and 1 according to their

priorities. The fi nal score for a particular benefi t or barrier is calculated by summing up the products

of rank scores and response numbers for all tools and projects.

Method 2.1 – Weighted ranking without RUG-ADL and Karnofsky

Based on the same reason as method 1.1, RUG-ADL and Karnofsky are excluded from this analysis.

The rest is the same as method 2.

Method 2.2 – Capped weighted ranking

In the analysis of methods 2 and 2.1, it was found that it is sometimes diffi cult to distinguish

between options, especially when the response rate for the particular tool or project is very low.

Multiple options may take the same rank. For example, ‘Enabling consistent care’ and ‘Improves

quality of care’ were ranked equally as second best benefi ts for Edmonton Symptom Assessment

System (ESAS). Bias will be created if both were given rank scores of 2 and the third best option

will be excluded. To solve these problems, a possible solution is to split the rank score evenly to

those options gaining the same rank and keep the total scores for one tool as 6 (3 + 2 + 1). In this

example, both benefi ts were given a score of 1, keeping the total score of the second best benefi ts

as 2 and the total score for all top benefi ts as 6.

The rest of the analysis is the same as method 2.

Method 2.3 – Capped weighted ranking without RUG-ADL and Karnofsky

Based on the same reason as method 2.1, RUG-ADL and Karnofsky are excluded from this analysis.

The rest is the same as method 2.2.

Method to classify palliative care service providers

Though each palliative care service provider has its own characteristics, it will be worthwhile to

classify them into a limited number of groups and to identify common themes within each group.

All perceived benefi ts, barriers and attitudes are considered as factors to group service providers.

With this many factors, it is not possible to classify service providers manually. Cluster analysis was

used to group service providers.

Due to the similarity of PCOC and LCP to the Pain Indicator Project, it is worthwhile to group service

providers according to their responses to PCOC and LCP, and their overall responses to all tools and

the overall project. The grouping results can be verifi ed against each other to ensure the groups are

classifi ed reasonably.

10

2.1 Literature review result

The literature suggested different defi nitions and types of clinical indicators (Travaglia & Debono

2009). Four types of indicators were identifi ed as suitable for consideration for this project:

Process

Measures of the quality of the care provided, including any element in the interaction with patients,

such as diagnosis and treatment. The aim is to measure whether clinicians are adhering to

(evidence-based) practices that achieve the best outcome for patients.

Outcome

Measures or approximations of the effects of care on the health status of patients and populations.

As multiple factors contribute to health care outcomes, evaluations of outcome indicators take into

account differences in case mix and controls over other covariates.

Symptom

Measures of specifi c aspects of care related to predetermined diseases.

Structure

Measures of the attributes of settings within which healthcare occurs, including material and human

resources and organisational structure.

Seventy-four literatures were identifi ed through searching the data bases. By screening abstracts,

35 were classifi ed as irrelevant to the project. The full text of 39 articles classifi ed as relevant were

reviewed according to protocol requirements and 22 more were identifi ed through reference-tracking

and reviewed as well.

Besides these academic literatures, guidelines and policies from government and non-government

agencies, including Australian Institute of Health and Welfare, the Australian Council on Healthcare

Standards, Australian and New Zealand Society of Palliative Medicine, Victorian Government, Palliative

Care Victoria, Palliative Care Outcomes Collaboration, Palliative Care Australia, were also reviewed.

A total of 113 indicators were identifi ed through the full text review process. After removal of

duplicated indicators by reviewing description and context of every indicator, 55 distinct indicators

were included in fi nal indicator set.

These indicators were grouped by types, settings and levels of detail.

Types are as defi ned above, namely process, outcome, symptom and structure.

Figure 1: Indicators by type

2. Results and discussion

Process 31

Outcome 7

Structure 1

Symptom 16

11

Among these four types, symptom and structure indicators were considered irrelevant.

Settings include ‘hospital’, ‘hospice’, ‘LTCF’ (long term caring facility) and ‘all’. Indicators designed

for ICU use are included into ‘hospital’ setting while nursing home is classifi ed into LTCF. An indicator

was classifi ed into one setting when it was either only discussed within that setting or recommended

by the author for the setting. The setting ‘all’ means that the indicators were not discussed for

particular settings in an article but should not be interpreted as the indicator being suitable to use

in all possible settings. In the case of an indicator being discussed in multiple settings separately in

different articles, it was classifi ed under ‘all’.

Figure 2: Indicators by setting

Levels of detail include ‘high’ and ‘low’ based on the indicator’s defi nition in the original article. An

indicator was classifi ed as ‘high’ when a detailed requirement was specifi ed for the way the tool

could be used or the indicator calculation method given; it was classifi ed as ‘low’ when details of its

implementation or calculation were not available.

Figure 3: Indicators by detail level

The project team selected a fi nal list of 29 indicators from which the expert panel could select the

fi nal group. Appendix 3 lists these candidate indicators.

All 32

LTCF 12

Hospice 4

Hospital 7

High 32Low 23

12

2.2 Expert panel result

2.2.1 Outcomes from round 1 – appropriateness

Voting result

The following nine indicators entered round 2 of voting with modifi cations of defi nition and/or

benchmark according to feedback from panel members.

Table 1: List of agreed indicators from round 1

ID Type Indicator name Mean

Standard

deviation

O1 Outcome Pain relief in specifi ed time 8.1 0.90

P1 Process Regular pain assessment 8.6 0.79

P2 Process Assessing pain for a new patient 9.0 0.00

P4 Process Providing a bowel regimen with an opioid 8.9 0.38

P6 Process Use of a validated pain scale 8.6 0.79

P8 Process Prescribing for breakthrough pain 8.4 0.53

P9 Process Documenting pain in end of life 7.9 0.69

P13 Process Scheduled pain medication for severe pain 7.9 0.90

P19 Process Documenting medicine used 8.4 0.98

Among all selected indicators, ‘Assessing pain for a new patient’ scored 9 by all raters. All factors

related to this indicator were marked as ‘Yes’ by all raters too, showing complete agreement in the

fi elds of validity, feasibility and generalisability for this indicator.

‘Scheduled pain medication for severe pain’ and ‘Documenting pain in end of life’ were the two

weakest indicators among those chosen. They all have a mean rating of 7.9, and only six out of

seven were marked ‘Yes’ for validity. All other indicators were given seven out of seven and ‘Yes’ for

validity, in other words, 100 per cent agreement.

The ratings for all indicators tend to fall in the higher score region, with a mean score of 7.4 and

standard deviation of 0.97. This is expected because the indicators are screened by the project

team. There are nine indicators classifi ed as having agreement with the strict rule, and six more will

fall into this category if the relaxed rule is applied. Since no more than 10 indicators were expected to

pass round 1 as defi ned in the terms of reference, the strict rule of agreement was used.

Modifi cations to defi nition and benchmarks

The defi nitions of some of the nine selected indicators were modifi ed following comments from the

expert panel in round 1. No changes in the benchmarks were recommended during round 1.

13

Table 2: List of changes to indicators from round 1

ID Indicator name Changes

O1 Pain relief in specifi ed time Numerator: added clarifi cation on ‘≤ 3’

Denominator: added ‘and the pain is identifi ed as a symptom’

P9 Documenting pain in end

of life

Numerator: added ‘The documentation should include

assessment using validated pain scales.’

P19 Documenting medicine

used

And complementary treatments also. This should be practice for

all medications and therapies in all settings.

Indicators to be included with the relaxed rule

Table 3: List of indicators complied with the relaxed rule from round 1

Count: 6

ID Type Mean

Standard

deviation

P5 Process Change pain regimen with severe sustained/

worsening pain 8.3 1.25

P10 Process Patient education 8.1 1.07

P18 Process Identifying cause of pain 7.9 1.46

P22 Process Assessing impact of pain 7.1 1.21

P23 Process Assessing effi cacy and side effects for new

opioid therapy

7.9 1.86

P24 Process Documenting pain management 7.9 1.46

Indicators P5 and P10 actually had higher average score than P9 and P13. They were excluded

because, although most raters rated them high enough, one rater gave a score less than 7. Although

one of our raters gave systematically low scores for all the indicators, it was not this rater’s score that

made both P5 and P10 fall out of the 7–9 range. Therefore, it is reasonable to conclude that these

two indicators cannot achieve strict agreement of appropriateness.

14

Highly discordant indicators

Table 4: List of highly discordant indicators from round 1

Count: 8


Standard

deviation

O4 Outcome Optimal pain management 5.7 2.36

O5 Outcome Effectiveness of treatment 6.0 2.83

P7 Process Re-assessment with change of pain regimen

within 4 hrs (inpatient)/next visit (outpatient) 6.4 2.82

P11 Process Carer satisfaction 5.9 2.41

P15 Process Pain treatment rate 6.0 2.24

P17 Process Pain documentation fl ow sheet 6.1 2.73

P20 Process Consistent opioid dose across setting 7.0 2.38

P21 Process Complete pain assessment rate 7.6 2.94

Among these eight indicators, it is evident that O4, O5, P7, P11, P15 and P17 are highly discordant

because of similar low average scores and high variance. On the other hand, P20 and P21 are

suspicious because their average scores are too high. The reason for classifying them as ‘highly

discordant’ is because the rater who gave systematically low scores, scored them extremely low,

1 for P21 and 2 for P20, while all other raters give them high scores within the 7–9 range. Further

clarifi cation from the rater took place without resulting in a change in overall scoring because

systematic low scoring did not result in rescaling of the scores to a signifi cant extent and the rater

answered ‘No’ for all the factors of these two indicators.

Indeterminate indicators

Table 5: List of indeterminate indicators from round 1

Count: 6


Standard

deviation

O2 Outcome Patient satisfaction 6.9 1.57

O3 Outcome Stable pain in end of life 6.1 2.27

P3 Process Staff education 7.3 1.38

P12 Process Patient satisfaction 7.4 1.27

P14 Process Quality improvement policy 7.4 1.51

P16 Process Pain management policy 7.3 1.70

Since ‘indeterminate’ covered all scenarios outside the other three defi ned classifi cations, there was

no particular scoring pattern observed.

17

Outcomes from round 2 – necessity

Voting result

The following six indicators were chosen from round 2 – necessity voting.

Table 6: List of agreed indicators from round 2


Standard

deviation

P1 Process Regular pain assessment 8.9 0.38

P2 Process Assessing pain for a new patient 9.0 0.00

P4 Process Providing a bowel regimen with an opioid 8.7 0.49

P6 Process Use of a validated pain scale 8.0 0.82

P8 Process Prescribing for breakthrough pain 8.6 0.79

P13 Process Scheduled pain medication for severe pain 8.3 0.49

Among all six chosen indicators, ‘Assessing pain for a new patient’ achieved maximum consensus

with all raters scoring 9. And all raters considered it as both fundamental and essential for consistent

quality of care. This indicator was the most agreed indicator in round 1 also.

The weakest supported indicator among the six selected was ‘Use of a validated pain scale’. It

had the lowest score (8.0) although it was rated third highest in round 1. And among the factors

considered, one rater didn’t consider it as fundamental, one rater didn’t consider it as essential

for consistent quality of care and a third rater answered no for both of them. This implied hidden

disagreement on its necessity, which was far from that expected.

As in the fi rst round, the ratings for all indicators tended to fall into the higher score region, with a

mean score of 8.2 and standard deviation of 0.63. The six selected indicators are identifi ed through

the ‘strict agreement rule’. All other three indicators will be considered as ‘necessary’ if the ‘relaxed

agreement rule’ is applied.

Modifi cations to defi nition and benchmarks

More comments were provided by raters during this round.

Table 7: List of changes to indicators from round 2

ID Indicator name Clarifi cation

O1 Pain relief in specifi ed time More detail in numerator:

For outpatients, if the pain regimen is changed or advice is given,

the measurement should be followed up by phone within 24 hours.

P1 Regular pain assessment This indicator needs to be further redeveloped.

P9 Documenting pain in end

of life

Numerator defi nition changed to:

Number of deceased patients with pain assessment documented

in last seven days of life. The documentation should include

assessment using validated pain scales.

P13 Scheduled pain

medication for severe pain

Denominator defi nition changed to:

Number of patients with severe pain documented with a

validated pain score.

16

Although indicator O1 was not selected, it is still worthwhile recording the clarifi cation for it.

For O1 ‘Pain-relief in specifi ed time’, a more detailed clarifi cation was needed to describe scenarios

to obtain a post-treatment pain score.

1. Inpatient without regular pain assessment: Use last measurement within 48 hours of admission.

2. Inpatient with regular pain assessment: Use average pain scores after last pain-related

prescription or treatment.

3. Outpatient with pain measured at each visit: Use measurement of the second visit. If pain regimen

is changed or advice is given, the measurement should be followed up by phone within 24 hours.

4. Outpatient without pain measured at each visit: This is defi nitely considered as a failure to meet

the requirement.

A home visit will be treated the same as an outpatient.

P2 ‘Assessing pain for a new patient’

One rater suggested changing the timeframe for inpatients to 24 hours. The benchmarking criteria

could be modifi ed during implementation without signifi cant effort required.

Indicators to be included with the relaxed rule

All nine proposed indicators would have been chosen if the relaxed rule was applied. The three

additional indicators were:

Table 8: List of indicators complied with the relaxed rule from round 2

Count: 3


Standard

deviation

O1 Outcome Pain relief in specifi ed time 7.6 1.13

P9 Process Documenting pain in end of life 7.3 1.25

P19 Process Documenting medicine used 7.6 0.98

Overall rating pattern

Overall, there is no systematic difference between the scoring patterns of individual raters. However,

a clear pattern associated with professional background emerged, which was not so obvious in

round 1 voting. Raters with a nursing background tended to give higher scores than those with a

medical background, no matter what their current appointments were. Total scores by clinicians

were all below 75 while total scores by nurses were all above 75. Although the sample size was too

small to prove this hypothesis, it is a topic worth further consideration.

2.2.2 Validating voting results

With the introduction of the shadow rater, there was no change of results in both rounds compared

with the original voting results.

17

2.2.3 Result and discussion

The expert panel showed high-level consensus over the fi nal set of indicators; the validating

mechanism of shadow voter did not introduce any variance to the fi nal result. Both the expert panel

and shadow voter followed the same rules defi ned prior to the voting process. The fi nal indicators are:

• regular pain assessment

• assessing pain for a new patient

• providing a bowel regimen with an opioid

• use of a validated pain scale

• prescribing for breakthrough pain

• scheduled pain medication for severe pain.

It is interesting that, within these six indicators, three of them were recommended by the ANZSPM

Clinical Indicators Working Group, although naming and defi nitions are slightly different. The

ANZSPM indicators are:

• pain intensity quantifi ed

• plan of care for pain

• aperients/laxatives initiated in patients on opioids.

It is very hard to justify to what extent the communication of these three indicators affects the

judgement or opinions of all involved experts. Despite this concern, the ANZSPM recommendation

could serve as evidence that the expert panel outcome from this project is aligned with outcomes

from this national organisation.

The backup grouping mechanism wasn’t used because the results were as expected. However, an

interesting phenomenon was observed. Experts with a nursing background tended to score higher

than those with a medical background. Further research will be required to explore this observation

as it may be very helpful for when implementing the recommended indicators.

2.3 Survey result

2.3.1 Respondent profi le

Response rate

Respondents invited 60

Respondents with answers 38 (63%)

In all, 38 out of 60 (63 per cent) invited services responded to the survey, which is an acceptable

response rate according to Mangione’s classifi cation of response rates to postal questionnaires

(Mangione 1995) and an excellent response rate according to general online surveys, which range

from 44 to 60 per cent (Cobanoglu et al. 2001; Cook et al. 2000).

18

Service type

Figure 4: Service types of respondents

*Vic DH SDF – Palliative care service delivery framework by the Department of Health

Compared with the Palliative care service delivery framework (SDF) (Aspex Consulting 2010),

community services were more highly represented in survey respondents while consultancy and

inpatient services were less represented. No publicly funded day hospice responded to the survey.

Survey respondents’ service delivery areas and regions are distributed similarly to the SDF mapping.

Ethics approval did not include direct contact with respondents to protect the confi dentiality of responses.

Service delivery areas

Figure 5: Service delivery areas of respondents*Vic DH SDF – Palliative care service delivery framework by the Department of Health

When compared with SDF data, the survey respondents’ distribution is similar to the whole

population of providers in terms of service delivery area. It is worth noting here that the survey asked

about regional service and rural service separately and some service providers deliver services in

multiple types of areas; this data is consolidated to be comparable to SDF data. Since the survey is

anonymous, it is possible that there might be errors when consolidating data. For agencies delivering

services in multiple types of areas, one will be classifi ed as metropolitan when it claims delivering

68% 13%

20%

18%

33% 4%

0% 20% 40% 60% 80% 100%

Survey

Vic DH SDF*

Metropolitan Regional and ruralState-wide

27%

33% 65%

5%

2%

68%

68%

42%

13%

20%

18%

33% 4%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Survey

Vic DH SDF*

Community service Consultancy service Inpatient service Day hospice

19

services to both metropolitan and regional areas. The general principle of assumption is an agency

will be based in the more populated area.

Service region

Figure 6: Health regions of respondents*Vic DH SDF – Palliative care service delivery framework by the Department of Health

Geographic distribution of survey respondents is similar to that from the SDF. The Royal District Nursing

Service (RDNS) is not counted, although it provides services for multiple agencies in metropolitan areas.

Staffi ng profi le

Figure 7: Staff numbers of respondents

From examining raw survey data, it is very possible that this question was interpreted into

two different meanings: number of dedicated palliative care staff and number of the hosting

organisation’s staff where the palliative care unit is part of a larger organisation. It is not possible to

distinguish between these two interpretations. This information is hence used for reference only.

0% 20% 40% 60% 80% 100%

Survey

Vic DH SDF*

16%

14%

16%

16%

11%

11%

13%

13%

13%

12%

13%

12%

13%

11%

Eastern Metropolitan Region Gippsland Region Grampians Region Hume Region Loddon Mallee Region North & West Metropolitan Southern Metropolitan Region

1

%

%5%

10%

Barwon-South Western Region

3%

3%

26%

5%

18%

24%

21%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

50+

20–50

10–20

6–10

3–6

2

1

%

%

20

2.3.2 Tools and quality improvement initiatives in use

Figure 8: Tools and quality programs in use by respondents

Respondents also listed many assessment tools in ‘other tools / quality improvement initiatives’

questions. Only one responded with NSAP, which is considered as quality improvement initiative.

2.3.3 Data entry

Table 9: Discipline

Time Who Number

Collection Nurse 95%

Other clinician 25%

Offi ce administrator 2%

Other (please specify) 7%

Patient/carer 9%

Administration Nurse 91%

Other clinician 18%

Offi ce administrator 12%

Other (please specify) 8%

Patient/carer 4%

Overall, most of the data collection and entry is done by nurses. Other clinicians did more at

collection than at administration. Administrative staff did more data entry at time of administration.

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

47%

47%

24%

24%

24%

66%

53%

79%

3%

3%

3%

Palliative Care OutcomesCollaboration (PCOC)

Edmonton Symptom AssessmentScale (ESAS)

Liverpool Care Pathway(LCP)

Pathway (MEOLCP)

RUG-ADL

Eastern Cooperative OncologyGroup (ECOG)

Other tool/qualityimprovement initiative No. 1

Other tool/qualityimprovement initiative No. 2

We do not use clinical tools

%

%

%

4

4

%

6

21

Answers to the ‘other’ option include data manager, medical intern, clinical documentation, project

worker, multidisciplinary team, person documenting in team meeting and progress notes.

It is possible that the difference between the time of collection and the time of administration is

not distinguished well because it is not possible for a patient/carer to enter data at the time of

administration. For this reason, a comparison between these two times is only suitable for reference

2.3.4 Top benefi ts and barriers

Table 10: Top three benefi ts and barriers

Method Top three benefi ts Top three barriers

Overall score Helps in prioritising care

Improves quality of care

Enables consistent care

Lack of IT support

Lack of ongoing funding to support data entry

Leads to extra work for staff

Original scores

w/o RK*


Demonstrates care practices

Helps in prioritising care


Lack of IT support


PCOC and LCP Enables benchmarking

Demonstrates care practices

Upskills staff



Lack of IT support

Weighted ranking

w/o RK*






Lack of IT support

Capped weighted

ranking


Enables benchmarking




Lack of IT support

Capped weighted

w/o RK*






Lack of IT support

* without RUG-ADL, Karnofsky

Overall the top perceived benefi ts were ‘Helps in prioritising care’, ‘Improves quality of care’ and

‘Enables consistent care’, which is consistent with the result for the combined assessment tools only.

Overall the top benefi ts perceived for quality improvement projects (PCOC and LCP) were ‘Enables

benchmarking’, ‘Demonstrates care practices’ and ‘Upskills staff’, which are consistent with the

top benefi ts of PCOC itself. However, when evaluating the benefi ts of LCP only, the perceptions

distributed too evenly because of the limited number of responders who only identifi ed top two

and bottom two benefi ts. The top two benefi ts of LCP are ‘Improves quality of care’ and ‘Enables

consistent care’ while the bottom two benefi ts are ‘Improves patient satisfaction’ and ‘Enables

benchmarking’.

Unlike the diversity of perceived benefi ts, the overall top perceived barriers are very consistent with

different evaluation methods. The top three barriers are ‘Leads to extra work for staff’, ‘Lack of IT

support’ and ‘Lack of ongoing funds to support data entry’ while the bottom three barriers are ‘Lack

of staff with appropriate skills’, ‘Not related to patient care’ and ‘Lack of support from management’.

22

It is worth noting that although the current LCP implementation doesn’t require IT support, it is still

rated as one of the top three.

2.3.5 Cluster analysis result

Three different types of services are identifi ed through cluster analysis. They are named as

enthusiast, conservative and cautious according to their characteristics.

Locality, service type, service area and organisation size do not seem have very strong infl uence

or correlation on perceptions. There is a pattern that more active groups have been using quality

projects or assessment tools for longer time.

The enthusiast group:

• mostly community services

• serves larger than average regional areas, fewer metropolitan or rural areas

• more likely to be medium sized

• highly regards the benefi ts and holds a positive view about related effort.

The conservative group:

• larger than average consultancy and inpatient services

• mostly serves metropolitan areas

• more likely to be large in size

• holds a positive view on barriers but is conservative on related benefi ts

• is able to take action once benefi ts are fully understood and accepted.

The cautious group:

• more than average inpatient services

• delivers more services to rural areas

• no particular size

• holds a moderate view on both benefi ts and barriers.

Psychological characteristics

By aggregating survey respondents’ responses to perceived benefi ts, barriers and judgement about

benefi t over effort with cluster analysis, responding services are divided into three groups.

These two charts demonstrate how these three groups are different from each other.

23

Figure 9: Perception profi les of respondent groups

Figure 10: Perception profi les of respondent groups – radar

According to each group’s scoring result, characteristics are summarised as follows. Please note

that the below descriptions are for the group as a whole, not for an individual organisation, although

they are helpful in identifying what kind of problems an organisation may have and for suggesting

corresponding solutions.

Patient satisfactionStaff satisfaction

Quality care

Consistent care

Prioritising care

Upskill staff

Demo care

Benchmarking

Low priority

Lack skillExtra work

Lack staff support

Not related to care

Lack IT

Low awareness

Lack funding

Lack management support

Good for organisation

Good for self

Good for patient

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Patient satisfaction

Staff satisfaction

Consistent care

Quality care

Prioritising care

Upskill staff

Demo care

Benchmarking

Low priority

Not related to care

Lack skill

Extra work

Lack staff support

Lack ITLow awareness

Lack funding

Lack management support

Good for organisation

Good for self

Good for patient

24

Group 1: Cautious

Those who hold a moderate view on most benefi ts and barriers. They believe quality improvement

projects are related to patient care but fi nd low awareness within the organisation and the lack of

IT support as major problems. Quality improvement projects are considered to mostly benefi t staff

members and patients rather than organisations.

Group 2: Conservative

Those who consider benefi ts as moderate and do not see most barriers as road blocks. Their major

concerns are the possible extra workload to staff members while there is no sustainable funding

to support this extra workload. They believe that the organisation and staff will benefi t more than

patients from quality improvement projects. And they don’t think patients will be more satisfi ed with

quality improvement projects though they believe these projects are related to patient care.

Group 3: Enthusiast

Those who highly appreciate benefi ts and do not consider most barriers as signifi cant. They believe

that all the efforts are worthwhile for the organisation, staff and patients. Quality improvement

projects are of high priority in these organisations and management give signifi cant support because

they believe it’s highly related to patient care.

Demographic characteristics

By analysing the characteristics of each group beside their perceptions, we are able to describe

them more accurately. Nine services were not able to be classifi ed into these three groups.

Table 11: Group vs service type

Group

Not

classifi ed 1 2 3 Total

Service

type

Community 6 4 4 12 26

Consultancy 3 0 1 1 5

Inpatient 0 3 2 2 7

Total 9 7 7 15 38

Figure 11: Distribution of groups by service type

0% 20% 40% 60% 80% 100%

Total

Group 3

Group 2

Group 1

Community service Consultancy service Inpatient service

25

Community services comprised 68 per cent (26/38) of total responses and 80 per cent (12/15) of the

responses within group 3. In addition, 46 per cent (12/26) of all community services fell into group 3.

It is safe to conclude that community services make up the majority of group 3.

Although the number of inpatient units is small, the trend is clear that the majority of inpatient units

fall into group 1 and that they account for 43 per cent (3/7) of all group 1 members.

The number of responses from consultancy services is limited, though neither of two valid responses

fall into group 1.

Table 12: Group vs region

Group

Not


Region Barwon-South Western 1 1 1 3 6

Eastern 0 0 2 0 2

Gippsland 2 2 1 1 6

Grampians 1 0 1 2 4

Hume 2 1 0 2 5

Loddon Mallee 2 1 0 2 5

North & West 0 1 0 4 5

Southern 1 1 2 1 5

Total 9 7 7 15 38

Figure 12: Distribution of groups by departmental region

0% 20% 40% 60% 80% 100%

Total

Group 3

Group 2

Group 1

Eastern Metropolitan Region Gippsland Region Grampians Region Hume Region Loddon Mallee Region North & West Metropolitan Southern Metropolitan Region


26

Fifty per cent (3/6) of responses from Barwon-South Western fall into group 3. One hundred per cent

(2/2) responses from Eastern Region fall into group 2. Thirty-three per cent (2/6) responses from

Gippsland fall into group 1. Fifty per cent (2/4) responses from Grampians fall into group 3. Forty per

cent (2/5) from Hume fall into group 3. Forty per cent (2/5) responses from Loddon Mallee fall into

group 3. Eighty per cent (4/5) from North & West Metropolitan area fall into group 3. Forty per cent

(2/5) responses from Southern Metropolitan Region fall into group 2.

Observable trends from valid responses show that Eastern and Southern services tend to fall into

group 2, Gippsland services tend to fall into group 1 and services in all other regions tend to fall

into group 3. Given the current overall response rate (63 per cent), we can conclude that there is no

obvious relationship pattern between region and group membership.

Table 13: Group vs service delivery areas

Group

Not


Service

delivery

Metro 1 2 4 5 12

Regional 4 2 2 9 17

Rural 7 4 2 8 21

Statewide 1 1 2

Figure 13: Service delivery areas of groups

The majority of all services tend to fall into group 3. This tendency is stronger for services serving

regional areas. Metropolitan services tend not to fall into group 1 and rural services tend not to fall into

group 2, when compared with all other services in the same area. But compared with the overall trend,

it is clear that metropolitan services tend to fall into group 2 while rural services tend to fall into group 1.

0% 20% 40% 60% 80% 100%

Total

Group 3

Group 2

Group 1

Metropolitan RuralStatementRegional

27

Table 14: Group vs staff number

Group

Not


Staff number 1 0 0 0 1 1

2 1 0 0 0 1

3–6 6 2 1 1 10

7–10 1 0 0 1 2

11–20 0 1 0 6 7

21–50 1 2 3 3 9

51+ 0 2 3 3 8

Total 9 7 7 15 38

Figure 14: Distribution of Groups by staff numbers

Comparing services of a similar size, organisations with a medium number of staff (6–20) are more likely

to fall into group 3 while organisations with fewer than six staff members are more likely to fall into group

1. Large organisations with 50 or more employees do not show trends between the three groups.

Comparing with overall trend, it is clear that medium-size organisations with 6–20 staff tend to

fall into group 3 while those with staff numbers larger than 20 tend to fall into group 2. Small

organisations with fewer than six staff members tend to spread over the three groups, although it

has a higher proportion in group 1.

0% 20% 40% 60% 80% 100%

Total

Group 3

Group 2

Group 1

1 3 to6 to

10 to 50+20 to2

28

Table 15: Group vs usage time of quality improvement projects

Group

Not


PCOC Less than 1 month

1–3 months 1 1 2

3–6 months 2 2

6–12 months 2 2

1–2 years 1 2 2 5

3–5 years 1 4 5

5+ years 2 2

Figure 15: PCOC participation time in groups

Most PCOC users fall into group 3 and show a large difference in duration of participation, from more

than fi ve years to just 1one to three months. Only two respondents fall into group 1 and they have

been using PCOC for six to 12 months.

0% 20% 40% 60% 80% 100%

Total

Group 3

Group 2

Group 1

4–6 months7–12 months

5+ years1–2 years3–5 years

Less than 1 month1–3 months

29

Table 16: Group vs usage time of LCP

Group

Not


LCP Less than 1 month

1–3 months 1 1

4–6 months 1 1

7–12 months 2 2

1–2 years

3–5 years 3 3

5+ years 2 2

Figure 16: LCP participation time of groups

None of group 1 is using the LCP now and 100 per cent (3/3) of group 2 members have been using

LCP for more than three years. Members of group 3 also spread across a long timeframe from just

one to three months to more than fi ve years. It is not possible to summarise the usage pattern of

LCP due to this limited sample size.

Overall, current data suggests that group 3 members are most likely to adopt new quality projects

while group 1 members are most unlikely to do so. Group 2 members may be willing to try. They

tend to continue using these projects once they realise the actual benefi ts from them but appear to

demonstrate a delay in starting.

0% 20% 40% 60% 80% 100%

Total

Group 3

Group 2

Group 1




30

Table 17: Group vs usage time of assessment tools

Overall

G1 G2 G3 Total

Less than 1 month 1 0 3 4

1–3 months 1 2 0 3

4–6 months 0 0 5 5

7–12 months 4 9 0 13

1–2 years 6 5 5 16

3–5 years 7 5 17 29

5+ years 6 3 17 26

Total 25 24 47

Figure 17: Assessment tools using time of groups

The questionnaire included an open question asking about other tools in use but not listed in the

questionnaire. The respondents referred mostly to assessment tools. These have been considered

as a group rather than individually.

Overall, respondents tended to have been using assessment tools for longer periods of time. More

than 50 per cent of services have been using cited assessment tool(s) for more than three years.

Group 3 members demonstrated the longest experience with assessment tools, with 72.4 per

cent of this group, compared with 33.3 per cent of group 2 members and 52 per cent of group 1

members listing experience with assessment tools for more than three years. Nine out of 24 (37.5

per cent) group 2 members have been using assessment tool(s) for six to 12 months while only four

out of 25 (16 per cent) group 1 members have been using assessment tool(s) for this time.

0% 20% 40% 60% 80% 100%

Total

Group 3

Group 2

Group 1




31

3.1 General recommendations

3.1.1 Minimum requirement

The resultant six indicators recommended for implementation by the Department of Health through

the PCCN were pertinent to two areas of pain management, namely pain assessment and analgesic

prescribing.

• pain assessment indicators

– use of a validated pain scale

– assessing pain for a new patient

– regular pain assessment

• analgesic prescribing indicators

– prescribing for breakthrough pain

– scheduled pain medication for severe pain

– providing a bowel regimen with an opioid.

According to the survey results, there is a likely correlation between the time of using assessment

tools and willingness to participate in new quality improvement programs. Therefore indicators in

the assessment group are recommended for initial implementation, before the analgesic prescribing

group, for organisations with limited resources. According to data requirements as defi ned in

Appendix 5, it is obvious that using a validated pain scale and accurate documentation are critical in

implementing the recommended indicators.

3.1.2 Individual organisation

Implementing new clinical indicators is a systematic process involving all levels of staff within an

organisation.

The process usually includes the following components:

• Organisational change

– Build effective structure within the organisation.

– Assign appropriate responsibilities.

– Ensure a consistent driving force for implementation.

• Building a culture of quality improvement

– Engage staff members to contribute to the implementation process.

– Stimulate passion from staff members.

• Education

– Increase awareness among related staff.

– Help staff members develop the required skills.

– Increase support from staff.

• Communication

– Facilitate common language (universal terminology) use among services.

– Increase awareness within the organisation.

– Increase support from management and staff.

3. Recommendations

32

The literatures often focuses on organisational change and culture building and consider education

and communication as subsections of these two factors (Davies et al. 2000; Ferlie & Shortell 2001;

Grol et al. 2002; Shortell 1995). The project team consider both education and communication as

factors of equal importance. As illustrated in Figure 18, these four components have an iterative

impact throughout the whole process of implementation, usually known as Plan-Do-Study-Act

(PDSA) or Plan-Do-Check-Act (PDCA), or the Deming cycle.

Figure 18: Factors and stages of implementation for individual organisations

Pilot IntegrationContinuous

improvement

Organisational change Plan Do

Culture building

Education

Communication Action Study

Generally, the process will be divided into three phases – piloting, formal integration and continuous

improvement.

Phase 1 – Pilot

Objectives

To establish essential infrastructure and process

To set up a performance baseline before implementation

To identify resource requirements for the following stages

Methodology

Involve all staff members in decision making

Assign project facilitators from both nursing and medical backgrounds to drive the process

Set up a regular education program to broaden the skill set of staff members

Adopt the Plan-Do-Study-Action method

Regularly refl ect on the effectiveness and effi ciency of the current process

Regularly improve the process according to refl ection

Conduct anonymous staff satisfaction evaluations

Phase completion criteria

Reach a team consensus on moving into the next stage

Ensure the required resources for the next stage are identifi ed and accessible

33

Expected outcomes

Obtain an initial evaluation result by comparing baseline data and end-of-stage data

Create a refi ned process of data collection

Establish baseline staff satisfaction

Optional outcomes

Develop a refi ned process of external data submission and reporting

Phase 2 – Formal integration

Objectives

To integrate the outcomes from the pilot phase into formal operation

To begin working collaboratively with other services

Methodology

Integrate indicator data collection into the current standard process and software, if applicable

Continue regular education programs and expand the audience to related professions to encourage

wider use of data

Convey improvement results regularly across the whole organisation

Conduct anonymous staff satisfaction evaluations


The process is successfully integrated into operation. Detailed criteria are to be defi ned by all team

members.

Expected outcomes

Improved evaluation results by comparing data at the beginning and end of stage

First internal formal report of performance against benchmarks

Improved satisfaction of staff

Optional outcomes

First informal report of indicators against other services

Phase 3 – Continuous improvement

Objectives

To improve quality of care continuously

To work collaboratively with other services on refi ning benchmarks and data defi nition

34

Methodology

Adopt the Plan-Do-Study-Action method

Regularly review benchmarks, data defi nition and collection methods

Introduce other indicators and related data collection

Convey results across the whole organisation and to other services


Nil

Expected outcomes

Continuously improved quality of care measured by existing and new indicators

Optional outcomes

Formal reports of indicators against other services

Indicative staff time requirement

It is estimated that during the pilot phase, the initial quarter will be mainly spent in establishing protocols

and gaining approvals from management and ethics, if required. For the following four quarters,

approximately 0.8 full-time equivalent (FTE) will be required for coordination. The integration phase

will require a similar but less time commitment. The continuous improvement phase will require the

least dedicated time, estimated at 0.2 EFT, since the process is already fi nalised and integrated.

Minor changes to the data collection process might be required during the phase. Contributions from

other staff are also required throughout the lifetime of the project. Table 18 gives a breakdown of the

estimated time requirements for both the coordination and all involved staff members.

Given the estimated effort, participating organisations are not encouraged to have dedicated staff

working solely on implementing the recommended indicators. As described above, the coordination

role is encouraged to be jointly taken by medical and nursing staffs that have clinical responsibilities

as well. While this is a slower process initially, it is more likely that, once established, the quality

improvement will be more sustainable within the organisation. It will become the normative practice

and relevant to clinicians.

Table 18: Indicative coordination time for the three phases

Pilot Integration Continuous improvement

Y1Q1 Y1Q2 Y1Q3 Y1Q4 Y2Q1 Y2Q2 Y2Q3 Y2Q4 Y3Q1 Y3Q2 Y3Q3 Y3Q4

FTE 0.4 0.8 0.8 0.8 0.8 0.7 0.7 0.2 0.2 0.2 0.2 0.2

35

Table 19: Breakdown of indicative time requirement

Phase Task

Coordination

(FTE)

Time commitment

from other staff

Other requirement

Pilot

Training and education 0.2 4 hours per month

Planning and progress tracking 0.2 2 hours per month

Regular meeting evaluation 0.2 1 hour per week

Data collection and analysis 0.2 Daily activity

Total 0.8

Integration Education 4 hours per month

Integration 0.4 Possible software

integration cost

Data collection and analysis 0.1 Daily activity

Evaluation 0.2

Total 0.7

Continuous

improvement

Process improvement 0.1 1 hour per week

Data collection/reporting/analysis 0.1 Daily activity

Total 0.2

3.1.3 Statewide implementation

In terms of statewide implementation, a similar route as within one organisation is recommended.

The stages for statewide implementation are modelling, expanding and collective improvement.

The relationship between developing individual organisations and a network is best demonstrated

in the following chart (Figure 19). Unlike the process for an individual organisation, there are no clear

boundaries between phases in terms of statewide implementation.

Figure 19: Stages of implementation for organisational level and network level

Organisation level Pilot IntegrationContinuous

improvement

Network level Modelling

Expanding

Collective

improvement

36

Stage 1: Modelling

Setting up a demonstration project involving model agencies will showcase the benefi ts derived from

implementing the recommended indicators. Ideally, the model agencies should be drawn from all

settings of palliative care service provision. As a minimum requirement, they should include service

types that encounter the majority of palliative care patients. Previous survey results indicate that

‘demonstrating care practice’ is one of the more highly appreciated benefi ts of quality improvement

projects. Based on the results of our cluster analysis, services in the enthusiast group are the

most appropriate to act as modelling agencies because of their willingness to use new quality-

improvement projects.

Another key purpose of modelling is to generate evidence for other services on how these indicators

could be integrated into different types of organisations. Again, a mini network of multiple agencies

covering most service types and delivery regions, rather than a stand-alone service, would be ideal

to develop solutions and to demonstrate best practices. The process of information sharing and

exchanging, especially that of how to submit data and report back, could be refi ned during this stage.

The earliest expected completion time of this stage of collaboration is at the end of at least

one participating service’s pilot phase. The latest expected completion time is at the end of

the integration phase of all participating services, though this should not be seen as a defi nite

requirement.

Although the data submission and reporting process is to be determined by the initial network

members, a feasible solution is to identify one member with appropriate resources to be the central

point for data reporting and defi ne this as part of its responsibilities. For this role, a minimum

resource requirement is having the capability of or access to database design and reporting.

Stage 2: Expanding

Near the end of stage 1, an initial pattern of communication and data submission/reporting will be

established and validated within the scope of the mini network. By this time, at least one service will

have already integrated the indicators into a formal operation process and at least one report will be

generated from the service showing the difference in care practice and performance compared with

baseline data.

Communication sessions would be required during this stage to convey successes and lessons

learnt from implementing indicators. Formats of communication include but are not limited

to educational presentations, seminars and publications. Both presentations and seminars

are expected to trigger interest and discussion within the Victorian palliative care sector while

publications from existing members are encouraged to stimulate broader interest and infl uence.

Publications are expected to be from diversifi ed perspectives to demonstrate benefi ts to patients, to

staff members of different professional backgrounds and to participating organisations.

Common language is another important factor to consider for communication. It is encouraged

that participating services use commonly accepted terminologies to convey results and to share

information. To help make indicators developed in this project a part of common language within

the Victorian palliative care sector, describing performance and improvement with these indicators

wherever possible will generate more awareness, familiarity and acceptance of them.

Concurrently, new services will be recruited into the network. Collaborations with other relevant

networks will be of mutual benefi t for this purpose. The Victorian Integrated Cancer Services are

ideal collaborators with a common interest in the quality of pain management. Existing members

could also use the ripple effect to infl uence non-member services with close working relationships.

37

Since the effort required to aggregate submitted data and reporting is expected to increase

signifi cantly during this stage, it is advisable to choose between two options:

a. to create a central role of data management and reporting

b. to divide the network into smaller circles and conduct a hierarchical data submission mechanism

in which each circle has its own data aggregation role and all fi nal data go to one of these central

roles for fi nal benchmarking and reporting.

Although a signifi cant difference is expected between these two modes, it is not very easy to

anticipate a dominant option at this time. The decision should be left to a consensus between all

participating services. It is advised that the decision should be made when the network expands

to more than eight member services or when it covers so many multiple health regions that the

workload becomes excessive to handle within one service’s capacity. The consortia may provide a

suitable structure for option b.

Stage 3: Collective improvement

Along with the expansion of data collection, the early adopters (members of the initial mini network)

will have completed integration already and be moving forward to a continuous improvement stage.

Increasing benchmarking criteria, refi ning data defi nition and introducing new indicators will be major

tasks of this phase for those who have completed integration and are requiring more space for

improvement.

Indicative staff time requirement

Unlike implementation within individual organisations, network-level coordination will require

dedicated staff working with on-site coordination staff from all participating service providers.

Network-level coordination will focus more on information and experience sharing along with data

aggregating and reporting back. More education work will be delivered by network coordinator(s).

Table 20 provides an indicative estimation of the time requirement.

Although individual organisations are not encouraged to have dedicated staff for implementing

recommended indicators as explained in section 3.1.2, network-level coordination may require initial

fi nancial support, sometimes known as seed funding, for the modelling stage. It is reasonable for

any funding body to have concerns about the validity, feasibility and impacts on health outcomes of

the recommended indicators and accompanied systems. In this case, external fi nancial support will

enable services participating in the modelling stage to generate solid evidence and therefore be able

to attract more funding from other resources. The PCCN is an ideal seed funding provider given its

role in overseeing clinical quality improvement programs and its existing knowledge of the project.

Table 20: Breakdown of indicative time requirement of network coordination

Phase Task Coordination resource (FTE)

Modelling Training and education 0.4

Information sharing 0.2

Data aggregating and reporting 0.2

Total 0.8

38

Phase Task Coordination resource (FTE)

Expanding Training and education 0.4

Information sharing 0.2


Total 0.8

Collective

improvement

Process revising 0.2


Total 0.4

3.2 Recommended solutions to barriers

3.2.1 General resource issues

The diversity of palliative care services providers in Victoria determines that resource availability

differs across the sector. Service providers are divided into three levels depending on resource levels.

Corresponding recommendations are provided accordingly.

Level 1: Limited

Services with limited resources often fi nd themselves unable to collect the data required for the

recommended indicators because of the staff or IT requirement, or both.

As identifi ed through the survey, there is a high correlation between services’ willingness to

participate quality projects and time for using assessment tools or quality programs. For services

with limited resources, it is recommended that they start with using validated assessment tools and

documenting assessment results.

Level 2: Medium

Services with a medium level of resources are capable of collecting part of the recommended

indicators but not all of them. It is recommended that services of this type put a higher priority on

the assessment indicators.

Level 3: Comprehensive

Services with comprehensive resources may have dedicated data management staff and IT support.

Services within this type are capable of collecting and reporting all recommended indicators.

3.2.2 Lack of IT support

It is in the best interests of all participating parties to record and submit data electronically.

Depending on the level of available IT support, services could use spreadsheets, stand-alone

database software or incorporate data within a patient information management system. Data

collecting time could also vary from retrospective, regular or real time.

3.2.3 Low awareness within an organisation

Increasing awareness is a long-term process involving all levels of staff.

For staff members involved directly in data collection, regular education sessions on the importance

of the data, the defi nitions of the terminology and the mechanics of the data collection method,

39

are recommended. Educational materials such as operational manuals and reminder cards will

be needed and could be developed by the coordinating service for distribution to all participating

services for daily use and reference.

This is recommended for management and staff related to, but not directly involved in, regular

communication about performance improvement as measured by these indicators.

The project team recommended that facilitators (see section 3.1.2) take responsibility for education

and communication as well.

3.2.4. Leads to extra work for staff

Communicating and demonstrating the benefi ts of implementing indicators will be important

to stimulate staff’s interest and willingness to use them, especially with evidence that it actually

increases effi ciency.

Encouraging staff participation from the very beginning stage of defi ning the new process will also

create a greater sense of ownership for all staff members and hence increase the perceived value of

implementing the indicators.

Developments in the skill sets of staff members through regular education and training programs

will increase effi ciency and hence lessen effort caused by data collection and entry.

It is recommended that services consider employing additional staff only when the above solutions

are exhausted and the workload is still beyond capacity.

3.2.5 Lack of ongoing funding to support data entry

Sustainability is one of the greatest concerns faced by all services. Given the reality that investment

in health is never adequate and quality improvement projects are not of high priority for funding

bodies, it is not plausible in most cases to rely on external funding to support data entry. However,

the technological issues that arise in data maintenance are beyond the scope of most practitioners

and will require central support from a coordinating central agency, either as part of the mini network

concept or from the department.

To minimise the impact on staff, it may help to:

a. stimulate staff members’ ownership towards quality improvement projects by increasing

involvement in all levels of decision making

b. convey more training sessions to broaden the skill sets of staff members

c. use quality improvement as a daily topic in all conversations and make it an essential part of the

operation.

Another alternative to introducing new funding is to share the cost and data entry burden within a

network or circle, as defi ned in section 3.1.3.

3.2.6 Lack of staff with the appropriate skills

Appropriate skills in this project include, but are not limited to, appropriate use of assessment tools,

understanding of statistics and computer literacy. Services will need to understand the personal

needs of education for each staff member and provide tailored education programs to improve skills.

Skill upgrading is of higher priority than introducing new staff solely dedicated to data entry. However,

a minimal EFT for data management is essential for quality control of data and generating meaningful

reports, benchmarking and other activities beyond the actual data entry.

40

Services are also encouraged to identify common themes of required training programs within the

network and hold education sessions for staff members from multiple services together.

Regular information sharing sessions could be used to share the experience of skill upgrading as well.

3.2.7 Lack of support from staff

This barrier is considered to link with barriers like ‘leads to extra work’, ‘lack of appropriate skills’ and

‘not related to patient care’, although further investigation is required to explore other possibilities.

As a general principle, sense of ownership and foreseeable benefi ts by participating services will

stimulate higher support from staff members. Ownership could be achieved by higher involvement in

decision making and designated responsibility to each individual while foreseeable benefi ts could be

provided through educating staff about the expected benefi ts from implementing the clinical indicators.

3.2.8 Lack of support from management

It is recommended that the PCCN organise a dedicated committee to discuss the possibility of establishing

an evaluation and accreditation program about quality improvement including clinical indicators. A formal

accreditation will stimulate management’s willingness to participate, although the program will need a long

time to be established. A feasible alternative is to set up an agenda for services to design the accreditation

program by themselves, which will stimulate higher involvement from management.

3.2.9 Low priority within our organisation

Priority issues may rise from staff, management or both. Survey results suggest that organisations

with a longer history of using assessment tools are more likely to participate in quality improvement

projects. Services are advised to enhance communications with other services that have more

experience with quality improvement to share experiences of implementation and the related benefi ts

that resulted from these activities.

3.2.10 Not related to patient care

Although the survey results suggest otherwise, the interviews show that staff members, both nursing

and medical, may consider data collection for quality improvement purposes as auxiliary and not

directly related to patient care, which is their core responsibility.

Services are advised to communicate with other services more frequently to understand the benefi ts

of implementing quality improvement projects for both patients and staff members.

3.3 Suggestions for services within each group characterised

in the survey

It is suggested that each organisation be willing to participate in building a profi le for itself and

choose a set of recommendations that best suit the organisation’s situation and needs.

3.3.1 General suggestions

A pre-implementation planning session involving all staff members is recommended. Key tasks of

this planning session are to:

• convey preliminary education about the clinical indicators for pain and potential benefi ts

• discuss the responsibilities of all staff members for implementation

• appoint an implementation committee

• appoint implementation coordinators from both nursing and medical backgrounds

• identify skill gaps of staff members and required training to fi ll the gaps.

41

The planning session can be divided into different parts depending on the time requirement and staff

availability.

A steering committee is suggested to provide high-level support and directions for implementation.

Ideally the steering committee should include representatives from clinical governance and other

related departments. In the case of small or medium organisations, members of the steering

committee could be from other organisations with related experience.

The implementation committee must include a decision-maker and selected coordination staff.

Key tasks of the committee are to:

• determine how to run the paper-based trial and how to integrate with the formal operation

• identify resource requirements for the trial and integration phases

• determine a timeline for the trial and integration phases, including termination criteria suitable for

the organisation

• liaise with management and report regularly to the steering committee if applicable

• deliver education sessions to increase awareness and to improve on the required skills

• deliver regular newsletters about progress and project achievements to all stakeholders.

3.3.2 The enthusiast group

The enthusiast organisations highly appreciate the benefi ts and do not consider the barriers as

signifi cant. They believe that all the efforts are worthwhile for the benefi t of the organisation, staff and

patients. Quality improvement projects are of high priority in these organisations and management

give high support because they believe it is highly related to patient care.

For this group, the barriers are ranked in the following order by decreasing signifi cance.

• Lack of IT support

• Low awareness within our organisation

• Leads to extra work for staff

• Lack of ongoing funding to support data entry

• Lack of staff with the appropriate skills

• Lack of support from staff

• Lack of support from management

• Low priority within our organisation

• Not related to patient care

Where palliative-dedicated software or a software module for palliative care is available, engaging software

vendors to integrate additional data collection and reporting requirements related to clinical indicators

would be ideal. When multiple services are using the same IT service provider, they will be able to share

the cost of integration or decrease the cost further for greater purchasing power. In the case of limited IT

resources, using a spreadsheet is recommended. Help from other participating organisations would be

very useful. There are examples of such collaborations at present within the palliative care sector.

Education and involvement are suggested ways to increase awareness, as recommended in section

3.2.3. Given this group has been actively working with other quality improvement projects, effort to

increase awareness might focus on improving the awareness of other highly related departments

within the organisation, such as pharmacy or social work. Regular newsletters are also suggested to

inform staff about progress and achievements.

42

One very important objective of all education and communication sessions is to emphasise the

benefi ts of implementing the clinical indicators for staff members and patients. This will effectively

reduce the perception of ‘extra workload’.

3.3.3 The conservative group

The conservative organisations consider benefi ts as moderate and do not see most barriers as

roadblocks. Their major concerns relate to the extra workload to staff members and the lack of

sustainable funding to support this extra workload. In addition, involved staff members may not be

supportive due to extra workload. They believe that the organisation and staff will benefi t more than

patients from quality improvement projects. Finally, they do not think that patients will be more satisfi ed

with quality improvement projects, though they believe these projects are related to patient care.











It is recommended that services within this group encourage clinical staff members to participate in

data entry so that data entry costs are minimised. It is important to communicate this as chances for

skill upgrading and decision-making involvement.

By emphasising the benefi ts of ‘demonstrating care practice’, ‘enables benchmarking’ and ‘helps in

prioritising care’ in education and communication sessions, the perception of ‘extra workload’ would

be reduced. As discussed in section 3.2.4, increasing involvement and upskilling staff are two other

effective ways to ease the stress of perceived additional burden.

Support from staff is essential to the success of any project. As discussed in section 3.2.7,

ownership and foreseeable benefi ts are important to include in decision making, education and

communication sessions.

3.3.4 The cautious group

The cautious organisations hold a moderate view on most benefi ts and barriers. They believe quality

improvement projects are related to patient care but fi nd low awareness within an organisation and

lacking IT support as major problems. Quality improvement projects are considered to mostly benefi t

staff members and patients rather than organisations.


43










Unlike the enthusiast group, low awareness in this group is more likely to be within the palliative care

service/unit itself. Additional education and sharing successful experiences from other services are

recommended before the pre-implementation planning session. The education should be delivered

to other related departments as well if they are part of a larger organisation.

It is highly possible this group does not own any specifi c palliative care software or software module.

Using a spreadsheet to collect data retrospectively is recommended to this group.

Staff skills could be improved by attending more experience-sharing sessions and more education

programs.

It is very likely that this group will only begin participating in the latter part of the expanding phase

as defi ned in section 3.1.3. However, promoting the use of independent indicators rather than

introducing the whole set of indicators will engage this group much earlier, especially by introducing

‘use of a validated pain scale’ and ‘assessing pain for a new patient’ as early as possible. Survey

results suggested that using pain tools long term is highly related to higher willingness to participate

in quality improvement projects.

44

• Medline (OvidSP) 1950 to October week 3, 2010

• Embase (OvidSP) 1980 to 2010, week 43

• CINAHL (EbscoHost)

• All EBM Reviews (OvidSP):

• Cochrane Database of Systematic Reviews

• ACP Journal Club

• DARE

• Cochrane Controlled Trial Register

• Cochrane Methodology Register

• Health Technology Assessment

• NHS Economic Evaluation Database

• Informit Health Collection (for Australian content)

• Scopus

• PubMed (deduplicated against Medline)

Appendix 1: Databases searched

45

No consistent subject heading term (for example, MeSH term) could be identifi ed for the topic of

clinical indicators, except within the CINAHL database. A broad and sensitive search strategy was

therefore constructed using textwords, truncated where appropriate. This was applied consistently

across all databases except PubMed (Table A1).

The PubMed search used a variation on this search. This was required for two reasons: PubMed

does not allow proximity limiters and a more sophisticated palliative care fi lter can be applied in this

database for the palliative care component (Table A2).

Table A1: Search strategy applied to all databases

Search History

#1 Clinical adj3 indicator*

#2 Quality adj3 indicator*

#3 #1 OR #2

#4 Pain

#5 Palliat* OR terminal OR end of life OR hospice*

#6 #3 AND #4 AND #5

Table A2: The PubMed search strategy incorporating the CareSearch palliative

care fi lter

# Searches Results

#1 clinical indicator*[tw] OR clinical quality indicator*[tw] OR clinical performance

indicator*[tw] OR quality indicator*[tw] 9,859

#2 pain[tw] 374420

#3 (advance care planning[mh] OR attitude to death[mh] OR bereavement[mh]

OR terminal care[mh] OR hospices[mh] OR life support care[mh] OR

palliative care[mh] OR terminally ill[mh] OR death[mh:noexp] OR palliat*[tw]

OR hospice*[tw] OR terminal care[tw] OR 1049-9091[is] OR 1472-684X[is]

OR 1357-6321[is] OR 1536-0539[is] OR 0825-8597[is] OR 1557-7740[is]

OR 1552-4264[is] OR 1478-9523[is] OR 1477-030X[is] OR 0749-1565[is]

OR 0742-969X[is] OR 1544-6794[is] OR 0941-4355[is] OR 1873-6513[is]

OR 0145-7624[is] OR 1091-7683[is] OR 0030-2228[is]) OR ((advance care

plan*[tw] OR attitude to death[tw] OR bereavement[tw] OR terminal care[tw]

OR life supportive care[tw] OR terminally ill[tw] OR palliat*[tw] OR hospice*[tw]

OR 1049-9091[is] OR 1472-684X[is] OR 1357-6321[is] OR 1536-0539[is]

OR 0825-8597[is] OR 1557-7740[is] OR 1552-4264[is] OR 1478-9523[is] OR

1477-030X[is] OR 0749-1565[is] OR 0742-969X[is] OR 1544-6794[is] OR

0941-4355[is] OR 1873-6513[is] OR 0145-7624[is] OR 1091-7683[is] OR 0030-

2228[is]) NOT Medline[sb]) AND English[la] 97635

#4 #1 AND #2 AND #3 37

#5 #4 NOT medline[sb] 1

Appendix 2: Terms used for literature search and results

46

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rial

pre

sent

n/a

90

%

P4

Pro

cess

Pro

vid

ing a

bow

el r

egim

en w

ith

an o

pio

id

Patients

pre

scrib

ed

op

ioid

s for

pain

who a

re a

lso p

rescrib

ed

ap

erients

/laxative

s for

constip

ation w

ithin

24 h

ours

of

their o

pio

id p

rescrip

tion,

where

ap

erients

/laxative

s a

re n

ot

contr

ain

dic

ate

d

Num

ber

of p

atients

pre

scrib

ed

op

ioid

s

for

pain

90

%

P5

Pro

cess

Change p

ain

regim

en w

ith s

eve

re

susta

ined

/wors

enin

g p

ain

Num

ber

of p

atients

whose o

pio

id p

rescrip

tion a

re c

hang

ed

with s

eve

re u

ncontr

olle

d p

ain

, or

the r

easons for

not

changin

g a

re d

ocum

ente

d

Tota

l num

ber

of p

atients

with s

eve

re

unco

ntr

olle

d p

ain

90

%

Appendix

3:

Candid

ate

indic

ato

rs f

or

exp

ert

panel

47

IDTyp

eIn

dic

ato

r n

am

eN

um

era

tor

Den

om

inato

r

PI ta

rget/

ben

ch

mark

P6

Pro

cess

Use o

f a v

alid

ate

d p

ain

scale

Num

ber

of p

atient

visits w

ith p

ain

score

s d

ocum

ente

d w

ith a

valid

ate

d p

ain

scale

(inclu

din

g t

he p

atients

who a

re c

ognitiv

ely

imp

aired

)

Num

bers

of p

atients

rep

ort

ing

pain

9

0%

P7

Pro

cess

Re-a

ssessm

ent

with c

hange o

f

pain

regim

en w

ithin

four

hours

(inp

atient)/n

ext

visit (outp

atient)

Num

ber

of p

atients

re-a

ssessed

within

four

hours

(in

patient)

or

on t

heir n

ext

visit (outp

atient) w

ith a

change o

f p

ain

regim

en

Num

ber

of p

atients

with p

ain

reg

imen

chang

ed

90

%

P8

Pro

cess

Pre

scrib

ing for

bre

akth

rough p

ain

Num

ber

of cases w

here

a s

hort

-acting o

pio

id is

pre

scrib

ed

up

on p

rescrip

tion o

f lo

ng-a

cting o

pio

ids

Tota

l num

ber

of cases w

ith lo

ng

-acting

op

ioid

pre

scrib

ed

90

%

P9

Pro

cess

Docum

enting p

ain

in e

nd

of lif

eN

um

ber

of d

eceased

patients

with p

ain

docum

ente

d in

last

thre

e o

ut

of seve

n d

ays

of lif

e

Num

ber

of d

eceased

patients

90

%

P10

Pro

cess

Patient

ed

ucation

Num

ber

of p

atients

who r

eceiv

ed

ed

ucation a

nd

/or

rela

ted

mate

rial a

bout

cancer

pain

and

pain

managem

ent

Num

ber

of to

tal p

atients

to

be t

reate

d

for

pain

90

%

P11

Pro

cess

Care

r satisfa

ction

Num

ber

of care

rs s

atisfi e

d w

ith p

ain

managem

ent

at

dis

charg

e (in

patient) o

r after

cert

ain

tim

es o

f consola

tions

(outp

atient)

Num

ber

of p

atients

receiv

ing

pain

manag

em

ent

75

%

P12

Pro

cess

Patient

satisfa

ction

Num

ber

of p

atients

satisfi e

d w

ith p

ain

managem

ent

at

dis

charg

e (in

patient) o

r after

cert

ain

tim

es o

f consola

tions

(outp

atient)

Num

ber

of p

atients

receiv

ing

pain

manag

em

ent

75

%

P13

Pro

cess

Sched

ule

d p

ain

med

ication for

seve

re p

ain

Num

ber

of p

atients

who h

ave

seve

re p

ain

with a

docum

ente

d

pain

managem

ent

med

ication s

ched

ule

Num

ber

of p

atients

with s

eve

re p

ain

90

%

P14

Pro

cess

Qualit

y im

pro

vem

ent

polic

yE

xis

tence o

f p

ain

managem

ent

qualit

y im

pro

vem

ent

polic

yn/a

80

%

P15

Pro

cess

Pain

tre

atm

ent

rate

Num

ber

of p

atients

with p

ain

are

tre

ate

d a

nd

the t

reatm

ents

are

docum

ente

d

Tota

l num

ber

of p

atients

with p

ain

10

0%

P16

Pro

cess

Pain

managem

ent

polic

yE

xis

tence o

f exp

licit p

ain

assessm

ent

and

managem

ent

polic

y

n/a

10

0%

P17

Pro

cess

Pain

docum

enta

tion fl o

w s

heet

Exis

tence o

f p

ain

docum

enta

tion fl o

w s

heet

n/a

75

%

P18

Pro

cess

Identify

ing c

ause o

f p

ain

Num

ber

of p

atients

with c

ause o

f p

ain

assessed

and

docum

ente

d t

ogeth

er

with p

ain

assessm

ent

Num

ber

of p

atients

assessed

fo

r p

ain

80

%

P19

Pro

cess

Docum

enting m

ed

icin

e u

sed

All

pain

-rela

ted

med

ication for

a p

atient

are

docum

ente

dn/a

10

0%

48

IDTyp

eIn

dic

ato

r n

am

eN

um

era

tor

Den

om

inato

r

PI ta

rget/

ben

ch

mark

P20

Pro

cess

Consis

tent

op

ioid

dose a

cro

ss

sett

ing

Exis

tence o

f d

ose c

onve

rsio

n d

ocum

ent

n/a

80

%

P21

Pro

cess

Com

ple

te p

ain

assessm

ent

rate

Num

ber

of p

atients

with C

OM

PLE

TE

pain

assessm

ent.

Location,

wors

t p

ain

, w

ors

enin

g facto

r, t

reatm

ent

effect,

tem

pora

l patt

ern

, q

ualit

y of p

ain

, p

ain

his

tory

, in

tensity,

imp

rovi

ng facto

r, d

ura

tion a

nd

belie

fs a

re r

eq

uired

to in

clu

de

in a

CO

MP

LE

TE

pain

assessm

ent

Num

ber

of p

atients

rep

ort

ing

pain

on a

dm

issio

n (in

patient) o

r fi r

st

visit

(outp

atient)

80

%

P22

Pro

cess

Assessin

g im

pact

of p

ain

Num

ber

of p

atients

with function im

pairm

ent

assessed

when

the p

atient

has m

od

era

te t

o s

eve

re p

ain

Num

ber

of p

atients

with m

od

era

te t

o

seve

re p

ain

80

%

P23

Pro

cess

Assessin

g e

ffi c

acy

and

sid

e e

ffect

for

new

op

ioid

thera

py

Num

ber

of p

atients

with n

ew

op

ioid

thera

py

who h

ave

effi c

acy

and

sid

e e

ffects

assessed

within

one m

onth

of

pre

scrip

tion

Num

ber

of p

atients

who

are

pre

scrib

ed

new

op

ioid

thera

py

90

%

P24

Pro

cess

Docum

enting p

ain

manag

em

ent

Num

ber

of p

atients

with p

hys

icia

n’s

att

em

pt

to r

ed

uce p

ain

show

ed

in m

ed

ical r

ecord

s if

the p

atient

has p

ain

Num

ber

of p

atients

with p

ain

10

0%

49

Your service

What is the name of your service or organisation?

What is your service type?

Palliative care community service

Day hospice

Palliative care consultancy service

Palliative care inpatient service

In which region does your organisation deliver service?


Eastern Metropolitan Region

Gippsland Region

Grampians Region

Hume Region

Loddon Mallee Region

North & West Metropolitan Region

Southern Metropolitan Region

Where does your organisation deliver service? (mark as many options as appropriate)

Metropolitan

Regional

Rural

Statewide

How many staff members are there in your organisation?

1

2

3–6

6–10

10–20

20–50

50+

Clinical tools used

Does your facility/service use any of the following clinical tools? (an answer is required;

mark as many options as appropriate)

Palliative Care Outcomes Collaboration (PCOC)

Edmonton Symptom Assessment Scale (ESAS)

Liverpool Care Pathway (LCP)

Modifi ed End of Life Care Pathway (MEOLCP)

RUG-ADL

Karnofsky

Eastern Cooperative Oncology Group (ECOG)

Brief Pain Inventory (BPI)

Other tool/ quality improvement initiative no. 1 (please specify): ..................................................................................

Other tool/ quality improvement initiative no. 2 (please specify): ..................................................................................

We do not use clinical tools

Appendix 4: Survey content

50

Details on PCOC usage

You have indicated that your facility/service uses PCOC.

How does your facility/service use PCOC? For data collecting or as clinical tools?

(mark as many options as appropriate)

Data collecting/reporting

Clinical tool

How long has your service been using this tool?

Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years

What is the prompt for the introduction of the tool? (mark as many options as appropriate)

New admission

Re-admission

Change in status

Discharge

Transfer to another service

Retrospective data collection

Other (please specify): ........................................................

...............................................................................................................

Who is responsible for data being entered into the tool at time of collection? (mark as many

options as appropriate)

Nurse

Other clinician

Offi ce administrator

Patient/carer


...............................................................................................................

Who is responsible for data being entered into the tool during administration? (mark as many


Nurse

Other clinician


Patient/carer


...............................................................................................................

51

The following are possible benefi ts associated with the PCOC clinical tool.

Please rate your level of agreement with these statements (1 = strongly disagree, 5 = strongly agree).

(1 = strongly disagree,

5 = strongly agree)

1 2 3 4 5 n/a

PCOC improves patient satisfaction

PCOC improves staff satisfaction

PCOC improves quality of care

PCOC enables consistent care

PCOC helps in prioritising care

PCOC upskills staff

PCOC enables benchmarking

PCOC demonstrates care practices

Other benefi ts of PCOC (please specify):............................................................

The following are possible barriers associated with the PCOC clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

PCOC is a low priority for our organisation

There is a lack of staff with the appropriate skills to use PCOC

Using PCOC leads to extra work for staff

There is a lack of support from staff in using PCOC

PCOC is not related to patient care

There is a lack of IT support with PCOC

There is a low awareness of PCOC within our organisation

There is a lack of ongoing funding to support data entry for PCOC

There is a lack of support from management for PCOC

Other barriers with PCOC (please specify): .......................................................

Please rate your level of agreement with the following statement: The benefi ts of PCOC outweigh the

effort involved in implementing and using the PCOC (1 = strongly disagree, 5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a

For your organisation

For yourself

For patients/families

52

Details on ESAS usage

You have indicated that your facility/service uses ESAS.

How does your facility/service use ESAS? For data collecting or as clinical tools?



Clinical tool


Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years


New admission

Re-admission

Change in status

Discharge




...............................................................................................................

Who is responsible for data being entered into the tool at time of collection? (mark as many


Nurse

Other clinician


Patient/carer


...............................................................................................................

Who is responsible for data being entered into the tool during administration?


Nurse

Other clinician


Patient/carer


...............................................................................................................

53

The following are possible benefi ts associated with the ESAS clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

ESAS improves patient satisfaction

ESAS improves staff satisfaction

ESAS improves quality of care

ESAS enables consistent care

ESAS helps in prioritising care

ESAS upskills staff

ESAS enables benchmarking

ESAS demonstrates care practices

Other benefi ts of ESAS (please specify): .............................................................

The following are possible barriers associated with the ESAS clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

ESAS is a low priority for our organisation

There is a lack of staff with the appropriate skills to use ESAS

Using ESAS leads to extra work for staff

There is a lack of support from staff in using ESAS

ESAS is not related to patient care

There is a lack of IT support with ESAS

There is a low awareness of ESAS within our organisation

There is a lack of ongoing funding to support data entry for ESAS

There is a lack of support from management for ESAS

Other barriers with ESAS (please specify): .........................................................

Please rate your level of agreement with the following statement: The benefi ts of ESAS outweigh the

effort involved in implementing and using the ESAS (1 = strongly disagree, 5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a


For yourself


54

Details on LCP usage

You have indicated that your facility/service uses LCP.

How does your facility/service use LCP? For data collecting or as clinical tools?



Clinical tool


Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years


New admission

Re-admission

Change in status

Discharge




...............................................................................................................

Who is responsible for data being entered into the tool at time of collection?


Nurse

Other clinician


Patient/carer


...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................

55

The following are possible benefi ts associated with the LCP clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

LCP improves patient satisfaction

LCP improves staff satisfaction

LCP improves quality of care

LCP enables consistent care

LCP helps in prioritising care

LCP upskills staff

LCP enables benchmarking

LCP demonstrates care practices

Other benefi ts of LCP (please specify):.................................................................

The following are possible barriers associated with the LCP clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

LCP is a low priority for our organisation

There is a lack of staff with the appropriate skills to use LCP

Using LCP leads to extra work for staff

There is a lack of support from staff in using LCP

LCP is not related to patient care

There is a lack of IT support with LCP

There is a low awareness of LCP within our organisation

There is a lack of ongoing funding to support data entry for LCP

There is a lack of support from management for LCP

Other barriers with LCP (please specify): ............................................................

Please rate your level of agreement with the following statement: The benefi ts of LCP outweigh the

effort involved in implementing and using the LCP (1 = strongly disagree, 5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a


For yourself


56

Details on MEOLCP usage

You have indicated that your facility/service uses MEOLCP.

How does your facility/service use MEOLCP? For data collecting or as clinical tools?



Clinical tool


Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years


New admission

Re-admission

Change in status

Discharge




...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................

57

The following are possible benefi ts associated with the MEOLCP clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

MEOLCP improves patient satisfaction

MEOLCP improves staff satisfaction

MEOLCP improves quality of care

MEOLCP enables consistent care

MEOLCP helps in prioritising care

MEOLCP upskills staff

MEOLCP enables benchmarking

MEOLCP demonstrates care practices

Other benefi ts of MEOLCP (please specify): .....................................................

The following are possible barriers associated with the MEOLCP clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

MEOLCP is a low priority for our organisation

There is a lack of staff with the appropriate skills to use MEOLCP

Using MEOLCP leads to extra work for staff

There is a lack of support from staff in using MEOLCP

MEOLCP is not related to patient care

There is a lack of IT support with MEOLCP

There is a low awareness of MEOLCP within our organisation

There is a lack of ongoing funding to support data entry for MEOLCP

There is a lack of support from management for MEOLCP

Other barriers with MEOLCP (please specify): ................................................

Please rate your level of agreement with the following statement: The benefi ts of MEOLCP outweigh

the effort involved in implementing and using the MEOLCP (1 = strongly disagree, 5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a


For yourself


58

Details on RUG-ADL usage

You have indicated that your facility/service uses RUG-ADL.

How does your facility/service use RUG-ADL? For data collecting or as clinical tools?



Clinical tool


Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years


New admission

Re-admission

Change in status

Discharge




...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................

59

The following are possible benefi ts associated with the RUG-ADL clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

RUG-ADL improves patient satisfaction

RUG-ADL improves staff satisfaction

RUG-ADL improves quality of care

RUG-ADL enables consistent care

RUG-ADL helps in prioritising care

RUG-ADL upskills staff

RUG-ADL enables benchmarking

RUG-ADL demonstrates care practices

Other benefi ts of RUG-ADL (please specify): ...................................................

The following are possible barriers associated with the RUG-ADL clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

RUG-ADL is a low priority for our organisation

There is a lack of staff with the appropriate skills to use RUG-ADL

Using RUG-ADL leads to extra work for staff

There is a lack of support from staff in using RUG-ADL

RUG-ADL is not related to patient care

There is a lack of IT support with RUG-ADL

There is a low awareness of RUG-ADL within our organisation

There is a lack of ongoing funding to support data entry for RUG-ADL

There is a lack of support from management for RUG-ADL

Other barriers with RUG-ADL (please specify): ...............................................

Please rate your level of agreement with the following statement: The benefi ts of RUG-ADL outweigh

the effort involved in implementing and using the RUG-ADL (1 = strongly disagree, 5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a


For yourself


60

Details on Karnofsky usage

You have indicated that your facility/service uses Karnofsky.

How does your facility/service use Karnofsky? For data collecting or as clinical tools?



Clinical tool


Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years


New admission

Re-admission

Change in status

Discharge




...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................

61

The following are possible benefi ts associated with the Karnofsky clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

Karnofsky improves patient satisfaction

Karnofsky improves staff satisfaction

Karnofsky improves quality of care

Karnofsky enables consistent care

Karnofsky helps in prioritising care

Karnofsky upskills staff

Karnofsky enables benchmarking

Karnofsky demonstrates care practices

Other benefi ts of Karnofsky (please specify): ...................................................

The following are possible barriers associated with the Karnofsky clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

Karnofsky is a low priority for our organisation

There is a lack of staff with the appropriate skills to use Karnofsky

Using Karnofsky leads to extra work for staff

There is a lack of support from staff in using Karnofsky

Karnofsky is not related to patient care

There is a lack of IT support with Karnofsky

There is a low awareness of Karnofsky within our organisation

There is a lack of ongoing funding to support data entry for Karnofsky

There is a lack of support from management for Karnofsky

Other barriers with Karnofsky (please specify): ...............................................

Please rate your level of agreement with the following statement: The benefi ts of Karnofsky outweigh

the effort involved in implementing and using the Karnofsky (1 = strongly disagree, 5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a


For yourself


62

Details on ECOG usage

You have indicated that your facility/service uses ECOG.

How does your facility/service use ECOG? For data collecting or as clinical tools?



Clinical tool


Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years

What is the prompt for the introduction of the tool?


New admission

Re-admission

Change in status

Discharge




...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................

63

The following are possible benefi ts associated with the ECOG clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

ECOG improves patient satisfaction

ECOG improves staff satisfaction

ECOG improves quality of care

ECOG enables consistent care

ECOG helps in prioritising care

ECOG upskills staff

ECOG enables benchmarking

ECOG demonstrates care practices

Other benefi ts of ECOG (please specify):

The following are possible barriers associated with the ECOG clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

ECOG is a low priority for our organisation

There is a lack of staff with the appropriate skills to use ECOG

Using ECOG leads to extra work for staff

There is a lack of support from staff in using ECOG

ECOG is not related to patient care

There is a lack of IT support with ECOG

There is a low awareness of ECOG within our organisation

There is a lack of ongoing funding to support data entry for ECOG

There is a lack of support from management for ECOG

Other barriers with ECOG (please specify):

Please rate your level of agreement with the following statement: The benefi ts of ECOG outweigh the

effort involved in implementing and using the ECOG (1 = strongly disagree, 5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a


For yourself


64

Details on BPI usage

You have indicated that your facility/service uses BPI.

How does your facility/service use BPI? For data collecting or as clinical tools?



Clinical tool


Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years



New admission

Re-admission

Change in status

Discharge




...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................

65

The following are possible benefi ts associated with the BPI clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

BPI improves patient satisfaction

BPI improves staff satisfaction

BPI improves quality of care

BPI enables consistent care

BPI helps in prioritising care

BPI upskills staff

BPI enables benchmarking

BPI demonstrates care practices

Other benefi ts of BPI (please specify):

The following are possible barriers associated with the BPI clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

BPI is a low priority for our organisation

There is a lack of staff with the appropriate skills to use BPI

Using BPI leads to extra work for staff

There is a lack of support from staff in using BPI

BPI is not related to patient care

There is a lack of IT support with BPI

There is a low awareness of BPI within our organisation

There is a lack of ongoing funding to support data entry for BPI

There is a lack of support from management for BPI

Other barriers with BPI (please specify):

Please rate your level of agreement with the following statement: The benefi ts of BPI outweigh the

effort involved in implementing and using the BPI (1 = strongly disagree, 5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a


For yourself


66

Details on other tool usage

You have indicated that your facility/service uses another tool.

How does your facility/service use this other tool? For data collecting or as a clinical tool?



Clinical tool


Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years


New admission

Re-admission

Change in status

Discharge




...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................

67

The following are possible benefi ts associated with this other clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

This other tool improves patient satisfaction

This other tool improves staff satisfaction

This other tool improves quality of care

This other tool enables consistent care

This other tool helps in prioritising care

This other tool upskills staff

This other tool enables benchmarking

This other tool demonstrates care practices

Other benefi ts of this other tool (please specify):

The following are possible barriers associated with this other clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

This other tool is a low priority for our organisation

There is a lack of staff with the appropriate skills to use this other tool

Using this other tool leads to extra work for staff

There is a lack of support from staff in using this other tool

This other tool is not related to patient care

There is a lack of IT support with this other tool

There is a low awareness of this other tool within our organisation

There is a lack of ongoing funding to support data entry for this

other tool

There is a lack of support from management for this other tool

Other barriers with this other tool (please specify):

Please rate your level of agreement with the following statement: The benefi ts of this other tool

outweigh the effort involved in implementing and using this other tool (1 = strongly disagree,

5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a


For yourself


68

Details on other tool usage no. 2

How does your facility/service use this second other tool? For data collecting or as a clinical

tool? (mark as many options as appropriate)


Clinical tool


Less than 1 month

1–3 months

3–6 months

6–12 months

1–2 years

3–5 years

5+ years



New admission

Re-admission

Change in status

Discharge




...............................................................................................................



Nurse

Other clinician


Patient/carer


...............................................................................................................

Who is responsible for data being entered into the tool during administration? (mark as many


Nurse

Other clinician


Patient/carer


...............................................................................................................

69

The following are possible benefi ts associated with this other clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

This other tool improves patient satisfaction

This other tool improves staff satisfaction

This other tool improves quality of care

This other tool enables consistent care

This other tool helps in prioritising care

This other tool upskills staff

This other tool enables benchmarking

This other tool demonstrates care practices

Other benefi ts of this other tool (please specify):

The following are possible barriers associated with this other clinical tool.



5 = strongly agree)

1 2 3 4 5 n/a

This other tool is a low priority for our organisation

There is a lack of staff with the appropriate skills to use this other tool

Using this other tool leads to extra work for staff

There is a lack of support from staff in using this other tool

This other tool is not related to patient care

There is a lack of IT support with this other tool

There is a low awareness of this other tool within our organisation

There is a lack of ongoing funding to support data entry for this

other tool

There is a lack of support from management for this other tool

Other barriers with this other tool (please specify):

Please rate your level of agreement with the following statement: The benefi ts of this other tool

outweigh the effort involved in implementing and using this other tool (1 = strongly disagree,

5 = strongly agree).


5 = strongly agree)

1 2 3 4 5 n/a


For yourself


70

Defi nitions and benchmarks of recommended indicators

As result of a rigid literature review and consensus of an expert panel, the below six indicators are

chosen to recommend to Victorian Department of Health.

Type Indicator name

Process Use of a validated pain scale

Process Assessing pain for a new patient

Process Regular pain assessment

Process Providing a bowel regimen with an opioid

Process Prescribing for breakthrough pain

Process Scheduled pain medication for severe pain

Documented: Within this fi le, ‘documented’ means being recorded in either paper-based forms or

electronically, which must be commonly accepted and used by all involved staff. A personal record

kept by one particular staff member will not be considered as documented.

HBPCCT: Hospital-based palliative care consultancy team. This concept is defi ned by the

Department of Health.

Inpatient: Inpatient in this document is defi ned as ‘inpatient admitted to palliative care bed card’.

Use of a validated pain scale

Numerator

Number of patient contacts with pain scores documented with a validated pain scale (including the

patients who are cognitively impaired).

Pain intensity should be quantifi ed using a standard and relevant instrument, such as a 0–10

numerical rating scale, a categorical scale (for example, none, mild, moderate and severe – as for

the Australian National–Subacute Non-Acute Patient – AN-SNAP, data collection around the PCOC),

or a pictorial scale (for example, Wong-Baker Faces Pain scale or for delirium and severe cognitive

impairment – ABBEY Pain Scale or PAINAD) (ANZSPM).

Denominator

Number of patient contacts requiring pain evaluation. To be counted, a patient should have reported

pain at admission (inpatient) or accepted referral (outpatient, community, HBPCCT) and the current

episode doesn’t end. Each patient contact is considered as requiring pain evaluation unless there is

a documented instruction not to do so.

For patients who are cognitively impaired, the pain is reported by a carer or alternate.

Benchmark

90 per cent

Appendix 5: Data specifi cation for clinical indicators for pain

71

Assessing pain for a new patient

Numerator

Number of patients with pain assessed within 48 hours of admission (inpatient) or for the fi rst visit

(outpatient, community, HBPCCT).

The patient should report pain at admission (inpatient) or referral (outpatient, community, HBPCCT).

The pain must be assessed with tools as described in the indicator ‘use of a validated pain scale’.

A patient is considered as new to the service when:

a. there is no previous record of the patient found, or

b. there is record of the patient but the patient was discontinued for palliative care.

The assessment result must be documented.

Denominator

Total number of patient admissions (inpatient) or accepted referrals (outpatient, community,

HBPCCT). To be counted, a patient should have reported pain at admission (inpatient) or accepted

referral (outpatient, community, HBPCCT).

Benchmark

90 per cent

Regular pain assessment

Numerator

Number of patients with a plan to re-assess pain, or who were regularly assessed for pain during the

course of their care.

The patients must have been assessed for pain as new patient; that is, the patient must have been

counted for numerator of indicator ‘assessing pain for a new patient’.

The plan must include either recurring planned reassessment time or a time interval between

assessments. The plan must be documented.

Comparing to extracting information from the assessment plan, it is more practical to count actual

pain assessments during the course of care. For inpatients, the maximum allowed time interval

between two pain assessments is 48 hours. For outpatients or community services, the pain must

be assessed with each visit to be counted within the numerator. To count a patient not meeting

these rules, there must be a clear documented instruction to discontinue the assessment.

Denominator

Number of patients who had pain assessed upon admission or fi rst contact.

This is the number as defi ned in the numerator section of the indicator ‘assessing pain for a new

patient’.

Benchmark

90 per cent

72

Providing a bowel regimen with an opioid

Numerator

Number of patients prescribed opioids for pain who are also prescribed aperients/laxatives

for constipation within 24 hours of their opioid prescription, where aperients/laxatives are not

contraindicated (ANZSPM).

Denominator

Number of patients prescribed opioids for pain.

By implication, a patient is only prescribed opioids when he/she has reported pain at admission

(inpatient) or accepted referral (outpatient, community, HBPCCT).

Benchmark

90 per cent

Prescribing for breakthrough pain

Numerator

Number of cases where a short-acting opioid is prescribed upon prescription of long-acting opioids.

Denominator

Total number of cases with a long-acting opioid prescribed.

A case is counted when a patient requires a new prescription or change of prescription.

Benchmark

90 per cent

Scheduled pain medication for severe pain

Numerator

Number of patients who have severe pain with a documented pain management medication

schedule.

Denominator

Number of patients with severe pain documented with a validated pain score.

The severe pain may be reported any time.

A validated pain score is as defi ned in the indicator ‘use of a validated pain scale’. Severe pain is

defi ned differently in different scales. For a common 0–10 scale, a score no less than 7 is defi ned as

severe.

Benchmark

90 per cent

73

Data elements required for each indicator

Indicator

Use o

f a v

alid

ate

d

pain

scale

Assessin

g p

ain

for

a n

ew

patie

nt

Reg

ula

r pain

assessm

en

t

Pro

vid

ing

a b

ow

el

reg

imen

with

an

op

ioid

Pre

scrib

ing

for

bre

akth

rou

gh

pain

Sch

ed

ule

d p

ain

med

icatio

n fo

r

severe

pain

Data elements

Patient ID x x

Episode ID x x

Episode status fl ag x x

Episode start time x x

Episode end time x x

Patient type

Patient referral time

Patient admission time

Pain reported at admission or

symptoms at admission

Contact ID x x x x x

Contact time x x

Pain evaluation fl ag x x

Pain scale 1 name

Pain scale 1 value

Pain scale 2 name

Pain scale 2 value

Pain scale 3 name

Pain scale 3 value

Severe pain fl ag x

Med: review fl ag x x x

Med: change of prescription fl ag x x x

Med: long-act opioid fl ag x x x

Med: short-act opioid fl ag x x x

Med: laxative fl ag x

74

Data elements defi nition

Patient ID As defi ned by agency

Episode ID As defi ned by agency

Episode status fl ag Ongoing/Finished

Episode start time Date + hour

Episode end time Date + hour

Patient type IP/OP/visit

Patient referral time Date + hour

Patient admission time Admission time for IP, referral acceptance time for OP

Pain reported at admission or

symptoms at admission

Yes/No, if it is only used for pain

Contact ID As defi ned by agency

Contact time Date + hour

Pain evaluation fl ag Required/Not required/Evaluated. Default is required. Can be

overridden to Not required/Evaluated. If any value in pain scales

changed, would automatically change to Evaluated

Pain scale 1 name As defi ned by agency

Pain scale 1 value As defi ned by agency





Severe pain fl ag Yes/No. Should be automatically calculated

Med: review fl ag Required/Not required/Reviewed. Default is Required

Med: change of prescription fl ag Yes/No

Med: long-act opioid fl ag Yes/No

Med: short-act opioid fl ag Yes/No

Med: laxative fl ag Yes/No

75

Aspex Consulting 2010, Palliative care service delivery framework and funding model – fi nal interim

report service delivery framework, State Government of Victoria, Melbourne.

Cobanoglu C, Warde B et al. 2001, ‘A comparison of mail, fax and web-based survey methods’,

International Journal of Market Research, vol. 43, no. 4, pp. 441–452.

Cook C, Heath F et al. 2000, ‘A meta-analysis of response rates in web- or internet-based surveys’,

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Davies HTO, Nutley SM et al. 2000, ‘Organisational culture and quality of health care’, Quality in

Health Care, vol. 9, no. 2, pp. 111–119.

Department of Health 2011, Strengthening palliative care: policy and strategic directions 2011–2015,

State Government of Victoria, Melbourne.

Ferlie EB, Shortell SM, 2001, ‘Improving the quality of health care in the United Kingdom and the

United States: a framework for change’, Milbank Quarterly, vol. 79, no. 2, pp. 281–315.

Fitch K, Bernstein SJ, et al. 2001, The RAND/UCLA appropriateness method user’s manual, RAND

Corporation, Santa Monica, CA.

Grol R, Baker R et al. 2002, ‘Quality improvement research: understanding the science of change in

health care’, Quality and Safety in Health Care, vol. 11, no. 2, pp. 110–111.

Mangione T 1995, Mail surveys: improving the quality, Sage, Thousand Oaks, CA.

S hortell SM 1995, ‘Assessing the impact of continuous quality improvement/total quality

management: concept versus implementation’, Health Services Research, vol. 30, no. 2, pp.

377–401.

Travaglia J, Debono D 2009, Clinical indicators: a comprehensive review of the literature, Centre for

Clinical Governance Research in Health, University of New South Wales, Sydney.

References

1304023 a systematic review for palliative care clinical indicators for...

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