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      Design and implementation of a decision aid for juvenile idiopathic arthritis medication choices

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          Abstract

          Background

          Randomized trials have demonstrated the efficacy of patient decision aids to facilitate shared decision making in clinical situations with multiple medically reasonable options for treatment. However, little is known about how best to implement these tools into routine clinical practice. In addition, reliable implementation of decision aids has been elusive and spread within pediatrics has been slow. We sought to develop and reliably implement a decision aid for treatment of children with juvenile idiopathic arthritis.

          Methods

          To design our decision aid, we partnered with patient, parent, and clinician stakeholders from the Pediatric Rheumatology Care and Outcomes Improvement Network. Six sites volunteered to use quality improvement methods to implement the decision aid. Four of these sites collected parent surveys following visits to assess outcomes. Parents reported on clinician use of the decision aid and the amount of shared decision making and uncertainty they experienced. We used chi-square tests to compare eligible visits with and without use of the decision aid on the experience of shared decision making and uncertainty.

          Results

          After 18 rounds of testing and revision, stakeholders approved the decision aid design for regular use. Qualitative feedback from end-users was positive. During the implementation project, the decision aid was used in 35% of visits where starting or switching medication was discussed. Clinicians used the decision aid as intended in 68% of these visits. The vast majority of parents reported high levels of shared decision making following visits with (64/76 = 84%) and without (80/95 = 84%) use of the decision aid ( p = 1). Similarly, the vast majority of parents reported no uncertainty following visits with (74/76 = 97%) and without (91/95 = 96%) use of the decision aid ( p = 0.58).

          Conclusions

          Although user acceptability of the decision aid was high, reliable implementation in routine clinical care proved challenging. Our parsimonious approach to outcome assessment failed to detect a difference between visits with and without use of our aid. Innovative approaches are needed to facilitate use of decision aids and the assessment of outcomes.

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          Most cited references29

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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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            Assessments of the extent to which health-care providers involve patients in decision making: a systematic review of studies using the OPTION instrument.

            We have no clear overview of the extent to which health-care providers involve patients in the decision-making process during consultations. The Observing Patient Involvement in Decision Making instrument (OPTION) was designed to assess this.
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              The Psychometric Properties of CollaboRATE: A Fast and Frugal Patient-Reported Measure of the Shared Decision-Making Process

              Background Patient-centered health care is a central component of current health policy agendas. Shared decision making (SDM) is considered to be the pinnacle of patient engagement and methods to promote this are becoming commonplace. However, the measurement of SDM continues to prove challenging. Reviews have highlighted the need for a patient-reported measure of SDM that is practical, valid, and reliable to assist implementation efforts. In consultation with patients, we developed CollaboRATE, a 3-item measure of the SDM process. Objective There is a need for scalable patient-reported measure of the SDM process. In the current project, we assessed the psychometric properties of CollaboRATE. Methods A representative sample of the US population were recruited online and were randomly allocated to view 1 of 6 simulated doctor-patient encounters in January 2013. Three dimensions of SDM were manipulated in the encounters: (1) explanation of the health issue, (2) elicitation of patient preferences, and (3) integration of patient preferences. Participants then completed CollaboRATE (possible scores 0-100) in addition to 2 other patient-reported measures of SDM: the 9-item Shared Decision Decision Making Questionnaire (SDM-Q-9) and the Doctor Facilitation subscale of the Patient’s Perceived Involvement in Care Scale (PICS). A subsample of participants was resurveyed between 7 and 14 days after the initial survey. We assessed CollaboRATE’s discriminative, concurrent, and divergent validity, intrarater reliability, and sensitivity to change. Results The final sample consisted of 1341 participants. CollaboRATE demonstrated discriminative validity, with a significant increase in CollaboRATE score as the number of core dimensions of SDM increased from zero (mean score: 46.0, 95% CI 42.4-49.6) to 3 (mean score 85.8, 95% CI 83.2-88.4). CollaboRATE also demonstrated concurrent validity with other measures of SDM, excellent intrarater reliability, and sensitivity to change; however, divergent validity was not demonstrated. Conclusions The fast and frugal nature of CollaboRATE lends itself to routine clinical use. Further assessment of CollaboRATE in real-world settings is required.
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                Author and article information

                Contributors
                513-636-2576 , Bill.Brinkman@cchmc.org
                Ellen.Lipstein@cchmc.org
                Janalee.taylor@cchmc.org
                pam.schoettker@cchmc.org
                katie.staun@gmail.com
                Karla.Jones@nationwidechildrens.org
                Sheetal.Vora@carolinashealthcare.org
                caldweca@musc.edu
                eroth@mcw.edu
                Gottlieb@northwell.edu
                nancy.griffin@cchmc.org
                carole.lannon@cchmc.org
                esi.morgan_dewitt@cchmc.org
                Journal
                Pediatr Rheumatol Online J
                Pediatr Rheumatol Online J
                Pediatric Rheumatology Online Journal
                BioMed Central (London )
                1546-0096
                5 June 2017
                5 June 2017
                2017
                : 15
                : 48
                Affiliations
                [1 ]ISNI 0000 0000 9025 8099, GRID grid.239573.9, , Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, ; 3333 Burnet Avenue, Cincinnati, OH 45229 USA
                [2 ]ISNI 0000 0001 2179 9593, GRID grid.24827.3b, , University of Cincinnati College of Design, Architecture, Art and Planning, ; 5470 Aronoff, Cincinnati, OH 45221 USA
                [3 ]ISNI 0000 0004 0392 3476, GRID grid.240344.5, , Nationwide Children’s Hospital, ; 700 Children’s Drive, Columbus, OH 43205 USA
                [4 ]ISNI 0000 0004 0411 7193, GRID grid.415907.e, , Levine Children’s Hospital, ; 1000 Blythe Blvd, Charlotte, NC 28203 USA
                [5 ]ISNI 0000 0001 2189 3475, GRID grid.259828.c, , Medical University of South Carolina, ; 171 Ashley Ave, Charleston, SC 29425 USA
                [6 ]ISNI 0000 0001 2111 8460, GRID grid.30760.32, , Medical College of Wisconsin, ; 8701 W Watertown Plank Rd, Milwaukee, WI 53226 USA
                [7 ]GRID grid.415338.8, , Cohen Children’s Medical Center of New York, ; 269-1 76th Ave, Queens, NY 11040 USA
                Article
                177
                10.1186/s12969-017-0177-x
                5460481
                70345625-d8de-47f3-afca-9a477d927fa2
                © The Author(s). 2017

                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
                : 19 May 2017
                : 30 May 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000133, Agency for Healthcare Research and Quality;
                Award ID: U19HS021114
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000025, National Institute of Mental Health;
                Award ID: K23MH083027
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100009633, Eunice Kennedy Shriver National Institute of Child Health and Human Development;
                Award ID: K23HD073149
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2017

                Pediatrics
                juvenile idiopathic arthritis,patient education,shared decision-making,decision aids

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