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      Implementing shared decision-making: consider all the consequences

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          Abstract

          Background

          The ethical argument that shared decision-making is “the right” thing to do, however laudable, is unlikely to change how healthcare is organized, just as evidence alone will be an insufficient factor: practice change is governed by factors such as cost, profit margin, quality, and efficiency. It is helpful, therefore, when evaluating new approaches such as shared decision-making to conceptualize potential consequences in a way that is broad, long-term, and as relevant as possible to multiple stakeholders. Yet, so far, evaluation metrics for shared decision-making have been mostly focused on short-term outcomes, such as cognitive or affective consequences in patients. The goal of this article is to hypothesize a wider set of consequences, that apply over an extended time horizon, and include outcomes at interactional, team, organizational and system levels, and to call for future research to study these possible consequences.

          Main argument

          To date, many more studies have evaluated patient decision aids rather than other approaches to shared decision-making, and the outcomes measured have typically been focused on short-term cognitive and affective outcomes, for example knowledge and decisional conflict. From a clinicians perspective, the shared decision-making process could be viewed as either intrinsically rewarding and protective, or burdensome and impractical, yet studies have not focused on the impact on professionals, either positive or negative. At interactional levels, group, team, and microsystem, the potential long-term consequences could include the development of a culture where deliberation and collaboration are regarded as guiding principles, where patients are coached to assess the value of interventions, to trade-off benefits versus harms, and assess their burdens—in short, to new social norms in the clinical workplace. At organizational levels, consistent shared decision-making might boost patient experience evaluations and lead to fewer complaints and legal challenges. In the long-term, shared decision-making might lead to changes in resource utilization, perhaps to reductions in cost, and to modification of workforce composition. Despite the gradual shift to value-based payment, some organizations, motivated by continued income derived from achieving high volumes of procedures and contacts, will see this as a negative consequence.

          Conclusion

          We suggest that a broader conceptualization and measurement of shared decision-making would provide a more substantive evidence base to guide implementation. We outline a framework which illustrates a hypothesized set of proximal, distal, and distant consequences that might occur if collaboration and deliberation could be achieved routinely, proposing that well-informed preference-based patient decisions might lead to safer, more cost-effective healthcare, which in turn might result in reduced utilization rates and improved health outcomes.

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          Most cited references29

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          Where is the evidence? A systematic review of shared decision making and patient outcomes.

          Despite widespread advocacy for shared decision making (SDM), the empirical evidence regarding its effectiveness to improve patient outcomes has not been systematically reviewed. The purpose of this study was to systematically review the empirical evidence linking patient outcomes and SDM, when the decision-making process has been explicitly measured, and to identify under what measurement perspectives SDM is associated with which types of patient outcomes (affective-cognitive, behavioral, and health). PubMed (through December 2012) and hand search of article bibliographies. Studies were included if they empirically 1) measured SDM in the context of a patient-clinician interaction and 2) evaluated the relationship between SDM and at least 1 patient outcome. Study results were categorized by SDM measurement perspective (patient-reported, clinician-reported, or observer-rated) and outcome type (affective-cognitive, behavioral, or health). Thirty-nine studies met inclusion criteria. Thirty-three used patient-reported measures of SDM, 6 used observer-rated measures, and 2 used clinician-reported measures. Ninety-seven unique patient outcomes were assessed; 51% affective-cognitive, 28% behavioral, and 21% health. Only 43% of assessments (n = 42) found a significant and positive relationship between SDM and the patient outcome. This proportion varied by SDM measurement perspective and outcome category. It was found that 52% of outcomes assessed with patient-reported SDM were significant and positive, compared with 21% with observer-rated and 0% with clinician-reported SDM. Regardless of measurement perspective, SDM was most likely to be associated with affective-cognitive patient outcomes (54%), compared with 37% of behavioral and 25% of health outcomes. The relatively small number of studies precludes meta-analysis. Because the study inclusion and exclusion criteria required both an empirical measure of SDM and an assessment of the association between that measure and a patient outcome, most included studies were observational in design. SDM, when perceived by patients as occurring, tends to result in improved affective-cognitive outcomes. Evidence is lacking for the association between empirical measures of SDM and patient behavioral and health outcomes. © The Author(s) 2014.
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            Shared Treatment Decision Making Improves Adherence and Outcomes in Poorly Controlled Asthma

            American Journal of Respiratory and Critical Care Medicine, 181(6), 566-577
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              “Many miles to go …”: a systematic review of the implementation of patient decision support interventions into routine clinical practice

              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
                glynelwyn@gmail.com
                froschd@pamfri.org
                kobrins@mail.nih.gov
                Journal
                Implement Sci
                Implement Sci
                Implementation Science : IS
                BioMed Central (London )
                1748-5908
                8 August 2016
                8 August 2016
                2015
                : 11
                : 114
                Affiliations
                [1 ]The Dartmouth Institute for Health Policy and Clinical Practice, 37 Dewey Field Road, Hanover, NH 03755 USA
                [2 ]Palo Alto Medical Foundation Research Institute, 795 El Camino Real, Palo Alto, CA 94301 USA
                [3 ]Department of Medicine, University of California, Los Angeles, CA 90024 USA
                [4 ]National Cancer Institute, 9609 Medical Center Drive, Rockville, MD 20850 USA
                Author information
                http://orcid.org/0000-0002-0917-6286
                Article
                480
                10.1186/s13012-016-0480-9
                4977650
                27502770
                cedd7c7e-27a0-4b86-97c1-a09ebae9acc3
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 12 February 2016
                : 1 August 2016
                Categories
                Debate
                Custom metadata
                © The Author(s) 2016

                Medicine
                collaborative deliberation,shared decision making,patient-centered care,implementation,practice improvement,quality improvement,multilevel,conceptual model,measurement

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