Ten years of the International Patient Decision Aid Standards Collaboration: evolution of the core dimensions for assessing the quality of patient decision aids

Conference name: The International Patient Decision Aid Standards (IPDAS) Collaboration's Quality Dimensions: Theoretical Rationales, Current Evidence, and Emerging Issues

Conference date: 1392012

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Abstract

In 2003, the International Patient Decision Aid Standards (IPDAS) Collaboration was established to enhance the quality and effectiveness of patient decision aids by establishing an evidence-informed framework for improving their content, development, implementation, and evaluation. Over this 10 year period, the Collaboration has established: a) the background document on 12 core dimensions to inform the original modified Delphi process to establish the IPDAS checklist (74 items); b) the valid and reliable IPDAS instrument (47 items); and c) the IPDAS qualifying (6 items), certifying (6 items + 4 items for screening), and quality criteria (28 items). The objective of this paper is to describe the evolution of the IPDAS Collaboration and discuss the standardized process used to update the background documents on the theoretical rationales, evidence and emerging issues underlying the 12 core dimensions for assessing the quality of patient decision aids.

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A systematic development process for patient decision aids

Angela Coulter, Diana Stilwell, Jennifer Kryworuchko … (2013)

Background The original version of the International Patient Decision Aid Standards (IPDAS) recommended that patient decision aids (PtDAs) should be carefully developed, user-tested and open to scrutiny, with a well-documented and systematically applied development process. We carried out a review to check the relevance and scope of this quality dimension and, if necessary, to update it. Methods Our review drew on three sources: a) published papers describing PtDAs evaluated in randomised controlled trials and included in the most recent Cochrane Collaboration review; b) linked papers cited in the trial reports that described how the PtDAs had been developed; and c) papers and web reports outlining the development process used by organisations experienced in developing multiple PtDAs. We then developed an extended model of the development process indicating the various steps on which documentation is required, as well as a checklist to assess the frequency with which each of the elements was publicly reported. Results Key features common to all patient decision aid (PtDA) development processes include: scoping and design; development of a prototype; ‘alpha’ testing with patients and clinicians in an iterative process; ‘beta’ testing in ‘real life’ conditions (field tests); and production of a final version for use and/or further evaluation. Only about half of the published reports on the development of PtDAs that we reviewed appear to have been field tested with patients, and even fewer had been reviewed or tested by clinicians not involved in the development process. Very few described a distribution strategy, and surprisingly few (17%) described a method for reviewing and synthesizing the clinical evidence. We describe a model development process that includes all the original elements of the original IPDAS criterion, expanded to include consideration of format and distribution plans as well as prototype development. Conclusions The case for including each of the elements outlined in our model development process is pragmatic rather than evidence-based. Optimal methods for ensuring that each stage of the process is carried out effectively require further development and testing.

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Assessing the Quality of Decision Support Technologies Using the International Patient Decision Aid Standards instrument (IPDASi)

Glyn Elwyn, Annette M. O'Connor, Carol Bennett … (2009)

Objectives To describe the development, validation and inter-rater reliability of an instrument to measure the quality of patient decision support technologies (decision aids). Design Scale development study, involving construct, item and scale development, validation and reliability testing. Setting There has been increasing use of decision support technologies – adjuncts to the discussions clinicians have with patients about difficult decisions. A global interest in developing these interventions exists among both for-profit and not-for-profit organisations. It is therefore essential to have internationally accepted standards to assess the quality of their development, process, content, potential bias and method of field testing and evaluation. Methods Scale development study, involving construct, item and scale development, validation and reliability testing. Participants Twenty-five researcher-members of the International Patient Decision Aid Standards Collaboration worked together to develop the instrument (IPDASi). In the fourth Stage (reliability study), eight raters assessed thirty randomly selected decision support technologies. Results IPDASi measures quality in 10 dimensions, using 47 items, and provides an overall quality score (scaled from 0 to 100) for each intervention. Overall IPDASi scores ranged from 33 to 82 across the decision support technologies sampled (n = 30), enabling discrimination. The inter-rater intraclass correlation for the overall quality score was 0.80. Correlations of dimension scores with the overall score were all positive (0.31 to 0.68). Cronbach's alpha values for the 8 raters ranged from 0.72 to 0.93. Cronbach's alphas based on the dimension means ranged from 0.50 to 0.81, indicating that the dimensions, although well correlated, measure different aspects of decision support technology quality. A short version (19 items) was also developed that had very similar mean scores to IPDASi and high correlation between short score and overall score 0.87 (CI 0.79 to 0.92). Conclusions This work demonstrates that IPDASi has the ability to assess the quality of decision support technologies. The existing IPDASi provides an assessment of the quality of a DST's components and will be used as a tool to provide formative advice to DSTs developers and summative assessments for those who want to compare their tools against an existing benchmark.

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“Many miles to go …”: a systematic review of the implementation of patient decision support interventions into routine clinical practice

Glyn Elwyn, Isabelle Scholl, Caroline Tietbohl … (2013)

Background Two decades of research has established the positive effect of using patient-targeted decision support interventions: patients gain knowledge, greater understanding of probabilities and increased confidence in decisions. Yet, despite their efficacy, the effectiveness of these decision support interventions in routine practice has yet to be established; widespread adoption has not occurred. The aim of this review was to search for and analyze the findings of published peer-reviewed studies that investigated the success levels of strategies or methods where attempts were made to implement patient-targeted decision support interventions into routine clinical settings. Methods An electronic search strategy was devised and adapted for the following databases: ASSIA, CINAHL, Embase, HMIC, Medline, Medline-in-process, OpenSIGLE, PsycINFO, Scopus, Social Services Abstracts, and the Web of Science. In addition, we used snowballing techniques. Studies were included after dual independent assessment. Results After assessment, 5322 abstracts yielded 51 articles for consideration. After examining full-texts, 17 studies were included and subjected to data extraction. The approach used in all studies was one where clinicians and their staff used a referral model, asking eligible patients to use decision support. The results point to significant challenges to the implementation of patient decision support using this model, including indifference on the part of health care professionals. This indifference stemmed from a reported lack of confidence in the content of decision support interventions and concern about disruption to established workflows, ultimately contributing to organizational inertia regarding their adoption. Conclusions It seems too early to make firm recommendations about how best to implement patient decision support into routine practice because approaches that use a ‘referral model’ consistently report difficulties. We sense that the underlying issues that militate against the use of patient decision support and, more generally, limit the adoption of shared decision making, are under-investigated and under-specified. Future reports from implementation studies could be improved by following guidelines, for example the SQUIRE proposals, and by adopting methods that would be able to go beyond the ‘barriers’ and ‘facilitators’ approach to understand more about the nature of professional and organizational resistance to these tools. The lack of incentives that reward the use of these interventions needs to be considered as a significant impediment.

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Author and article information

Contributors

Robert J Volk

Hilary Llewellyn-Thomas

Dawn Stacey

Glyn Elwyn

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Journal ID (nlm-ta): BMC Med Inform Decis Mak

Journal ID (iso-abbrev): BMC Med Inform Decis Mak

Title: BMC Medical Informatics and Decision Making

Publisher: BioMed Central

ISSN (Electronic): 1472-6947

Publication date Collection: 2013

Publication date (Electronic): 29 November 2013

Volume: 13

Issue: Suppl 2

Page: S1

Affiliations

[1 ]Department of General Internal Medicine, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Houston, Texas 77230 USA

[2 ]Department of Community and Family Medicine, The Geisel School of Medicine at Dartmouth, Hanover, NH 03755 USA

[3 ]The Dartmouth Institute for Health Policy and Clinical Practice, The Geisel School of Medicine at Dartmouth, Hanover, NH 03755 USA

[4 ]School of Nursing, University of Ottawa, 451 Smyth Road (RGN Room 1118), Ottawa, Ontario, K1H 8M5, Canada

[5 ]Clinical Epidemiology Program, Ottawa Hospital Research Institute, 501 Smyth Road, Box 201B, Ottawa, Ontario K1H 8L6, Canada

[6 ]Cochrane Institute of Primary Care and Public Health, Cardiff University School of Medicine, Health Park, CF14 4YS, UK

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Publisher ID: 1472-6947-13-S2-S1

DOI: 10.1186/1472-6947-13-S2-S1

PMC ID: 4044280

PubMed ID: 24624947

SO-VID: d7f3c2ae-768d-4a3f-8b5e-8b9aac117ca5

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This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Conference name: The International Patient Decision Aid Standards (IPDAS) Collaboration's Quality Dimensions: Theoretical Rationales, Current Evidence, and Emerging Issues

Ten years of the International Patient Decision Aid Standards Collaboration: evolution of the core dimensions for assessing the quality of patient decision aids

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Most cited references 21

A systematic development process for patient decision aids

Assessing the Quality of Decision Support Technologies Using the International Patient Decision Aid Standards instrument (IPDASi)

“Many miles to go …”: a systematic review of the implementation of patient decision support interventions into routine clinical practice

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