140
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

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

      review-article
      1 , , 2 , 3 , 1 , 1 , 4 , 5 , 6 , 7 , 8 , 3
      BMC Medical Informatics and Decision Making
      BioMed Central
      The International Patient Decision Aid Standards (IPDAS) Collaboration's Quality Dimensions: Theoretical Rationales, Current Evidence, and Emerging Issues

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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.

          Related collections

          Most cited references54

          • Record: found
          • Abstract: found
          • Article: not found

          Conceptualization and measurement of organizational readiness for change: a review of the literature in health services research and other fields.

          Health care practitioners and change experts contend that organizational readiness for change is a critical precursor to successful change implementation. This article assesses how organizational readiness for change has been defined and measured in health services research and other fields. Analysis of 106 peer-reviewed articles reveals conceptual ambiguities and disagreements in current thinking and writing about organizational readiness for change. Inspection of 43 instruments for measuring organizational readiness for change reveals limited evidence of reliability or validity for most publicly available measures. Several conceptual and methodological issues that need to be addressed to generate knowledge useful for practice are identified and discussed.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

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

            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.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Implementing shared decision making in the NHS.

                Bookmark

                Author and article information

                Contributors
                Conference
                BMC Med Inform Decis Mak
                BMC Med Inform Decis Mak
                BMC Medical Informatics and Decision Making
                BioMed Central
                1472-6947
                2013
                29 November 2013
                : 13
                : Suppl 2
                : S14
                Affiliations
                [1 ]Cochrane Institute of Primary Care and Public Health, Cardiff University School of Medicine, Heath Park, CF14 4YS, UK
                [2 ]Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Martinistr. 52, D - 20246 Hamburg, Germany
                [3 ]Department of Health Services Research, Palo Alto Medical Foundation Research Institute, 795 El Camino Real, Palo Alto, California, 94301, USA
                [4 ]Office of Professional Education and Outreach, The Dartmouth Institute of Health Policy and Clinical Practice, 46 Centerra Parkway, Suite 203, Lebanon, New Hampshire, 03766, USA
                [5 ]Knowledge Transfer and Health Technology Assessment Research Group, Research Centre of Centre Hospitalier Universitaire de Québec, Hôpital Saint-François D'Assise, 10, rue de l’Espinay, Québec, QC, G1L 3L5, Canada
                [6 ]Department of General Practice, School CAPHRI, Peter Debyeplein 1, 6229 HA, Maastricht, The Netherlands
                [7 ]University of North Carolina, Campus Box 7110, Chapel Hill, North Carolina, 27599, USA
                [8 ]Informed Medical Decisions Foundation, 40 Court Street, Suite 300, Boston, Massachusetts, 02108, USA
                Article
                1472-6947-13-S2-S14
                10.1186/1472-6947-13-S2-S14
                4044318
                24625083
                fe1ab821-bcd3-4564-bf29-12eb1c84dca1
                Copyright © 2013 Elwyn et al; licensee BioMed Central Ltd.

                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.

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

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

                Comments

                Comment on this article