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      The Benefits and Challenges of Using Patient Decision Aids to Support Shared Decision Making in Health Care

      1 , 1 , 1 , 1
      JCO Clinical Cancer Informatics
      American Society of Clinical Oncology (ASCO)

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          Abstract

          Shared decision making (SDM) and patient-centered care require patients to actively participate in the decision-making process. Yet with the increasing number and complexity of cancer treatment options, it can be a challenge for patients to evaluate clinical information and make risk–benefit trade-offs to choose the most appropriate treatment. Clinicians face time constraints and communication challenges, which can further hamper the SDM process. In this article, we review patient decision aids (PDAs) as a means of supporting SDM by presenting clinical information and risk data to patients in a format that is accessible and easy to understand. We outline the benefits and limitations of PDAs as well as the challenges in their development, such as a lengthy and complex development process and implementation obstacles. Lastly, we discuss future trends and how change on multiple levels—PDA developers, clinicians, hospital administrators, and health care insurers—can support the use of PDAs and consequently SDM. Through this multipronged approach, patients can be empowered to take an active role in their health and choose treatments that are in line with their values.

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          Most cited references37

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          Advances in prospect theory: Cumulative representation of uncertainty

          Journal of Risk and Uncertainty, 5(4), 297-323
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            A systematic development process for patient decision aids

            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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              Presenting quantitative information about decision outcomes: a risk communication primer for patient decision aid developers

              Background Making evidence-based decisions often requires comparison of two or more options. Research-based evidence may exist which quantifies how likely the outcomes are for each option. Understanding these numeric estimates improves patients’ risk perception and leads to better informed decision making. This paper summarises current “best practices” in communication of evidence-based numeric outcomes for developers of patient decision aids (PtDAs) and other health communication tools. Method An expert consensus group of fourteen researchers from North America, Europe, and Australasia identified eleven main issues in risk communication. Two experts for each issue wrote a “state of the art” summary of best evidence, drawing on the PtDA, health, psychological, and broader scientific literature. In addition, commonly used terms were defined and a set of guiding principles and key messages derived from the results. Results The eleven key components of risk communication were: 1) Presenting the chance an event will occur; 2) Presenting changes in numeric outcomes; 3) Outcome estimates for test and screening decisions; 4) Numeric estimates in context and with evaluative labels; 5) Conveying uncertainty; 6) Visual formats; 7) Tailoring estimates; 8) Formats for understanding outcomes over time; 9) Narrative methods for conveying the chance of an event; 10) Important skills for understanding numerical estimates; and 11) Interactive web-based formats. Guiding principles from the evidence summaries advise that risk communication formats should reflect the task required of the user, should always define a relevant reference class (i.e., denominator) over time, should aim to use a consistent format throughout documents, should avoid “1 in x” formats and variable denominators, consider the magnitude of numbers used and the possibility of format bias, and should take into account the numeracy and graph literacy of the audience. Conclusion A substantial and rapidly expanding evidence base exists for risk communication. Developers of tools to facilitate evidence-based decision making should apply these principles to improve the quality of risk communication in practice.
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                Author and article information

                Journal
                JCO Clinical Cancer Informatics
                JCO Clinical Cancer Informatics
                American Society of Clinical Oncology (ASCO)
                2473-4276
                December 2018
                December 2018
                : 2
                : 1-10
                Affiliations
                [1 ]Anshu Ankolekar, Andre Dekker, and Rianne Fijten, Maastricht University Medical Centre, Maastricht; and Adriana Berlanga, Maastricht University, Maastricht, the Netherlands.
                Article
                10.1200/CCI.18.00013
                30652607
                b98ded61-ef96-4ddc-9d18-ed5852fd718c
                © 2018
                History

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