Shared Decision Making Tools Implemented in the EHR: A Scoping Review Protocol

Title Shared Decision Making Tools Implemented in the EHR: A Scoping Review Protocol Authors Joni H. Pierce, Jorie M. Butler, Kensaku Kawamoto, Guilherme Del Fiol, Mary M. McFarland, Charlene R. Weir DOI: 10.26052/0D-TRJS-7QGE Review team members organizational affiliation Joni H. Pierce. Biomedical Informatics, University of Utah Jorie M. Butler. Biomedical Informatics, University of Utah Kensaku Kawamoto. Biomedical Informatics, University of Utah Guilherme Del Fiol. Biomedical Informatics, University of Utah Mary M. McFarland. Eccles Health Sciences Library, University of Utah Charlene R. Weir. Biomedical Informatics, University of Utah Primary research question: What are the characteristics of shared decision making (SDM) applications implemented and adopted within an electronic health record (EHR)? For the purpose of the scoping review we will consider the PICO Statement (patient/problem, intervention, comparators, and outcomes) (Table 1). Table 1 PICO Statement CATEGORY Patient/Population/Problem Interventions Comparators Outcomes ITEMS Patients where a clinical decision is being made in conjunction with a provider who is affiliated with a healthcare system that uses an EHR. Point of care digital shared decision-making tools that have been integrated into the EHR. . Integration may include full or partial EHR workflow implementation of shared decision making solutions. Multiple deployment situations such as single interaction, multiinteraction and ongoing decision making scenarios. None or traditional point of clinical care decision making Patient Level Outcomes Attitude toward SDM tools SDM tool use and adoption Patient satisfaction Decision regret (distress, remorse, personal values alignment) Relationship with clinician Clinical outcomes Medication adherence Treatment plan adherence Type of Study Clinical measures Clinician Level Outcomes Attitude toward SDM tools SDM tool use and adoption Workflow productivity User satisfaction with tool Time impact Clinical burnout Communication with patients Patient screening decisions Shared Decision Making Tool Implementation Outcomes Implementation methods Workflow design and presentation Obstacles to tool use and uptake Adoption rates Sustainability metrics Feasibility metrics Experimental, quasi-experimental, qualitative, ethnographic, and psychometric studies are included. Also included are meta-analysis and systematic reviews. Purpose of scoping study We intend to map the published literature for EHR integrated shared decision making tools that are used in point of care decision making between clinicians and patients. The purpose is to understand the scope and study characteristics for the published literature focused on digital shared decision making tools that have been implemented into an EHR use workflow. Since the purpose of a scoping review is to assess a broad range of research on a topic iteratively, we do not intend to limit the study population. Rationale for scoping study Effective and pragmatic shared decision-making tools continue to lag as a routine and ubiquitous standard of care (Legare & Witteman, 2013). In the current era of widespread adoption of EHR tools, there is an opportunity to explore the published research in order to identify the impact of EHR integrated shared decision making tools more directly (Day et al., 2019). Within this scoping review we intend to identify themes that are key areas of focus for policy makers, healthcare innovators, clinicians, patients and researchers. A number of systematic reviews have been published on the topic of shared decision making (Shay & Lafata, 2015). However, we were unable to identify any reviews in the published literature that specifically address EHR integrated shared decision making applications. Furthermore, despite the interest in incorporating shared decision making into the care process, a variety of obstacles including technical, logistical and psychological continue to impede progress. Many of the current research papers identify a number of barriers to adoption which are key areas for future research studies. Future research should identify those processes and methods that lead to greater overall adoption and shared decision making success (Legare & Witteman, 2013). Defining Shared Decision Making (SDM) For this scoping review we will use the definition for shared decision making from the National Academy of Medicine (Alston, 2014). SDM is the process of communication, deliberation, and decision making during which: • One or more clinicians share with the patient information about relevant testing or treatment options, including the severity and probability of potential harms and benefits and alternatives of these options given the specific nature of the patient’s situation; • The patient explores and shares with the clinician(s) his or her preferences regarding these harms, benefits, and potential outcomes; and • Through an interactive process of reflection and discussion, the clinician(s) and patient reach a mutual decision about the subsequent treatment or testing plan. Methods We will conduct our scoping review with guidance from The Joanna Briggs Institute (Peters MDJ, 2020) utilizing Arksey's five stages framework: 1) identifying the research question, 2) identifying relevant studies, 3) study selection, 4) charting the data and 5) collating, summarizing and (Tricco et al., 2018) reporting the results (Arksey & O'Malley, 2005). For transparency and reproducibility, we'll adhere to the PRISMA-ScR reporting guidelines for our protocol and manuscript (Tricco et al., 2018). All changes from scoping protocol methodology will be acknowledged and defined in the manuscript. Literature searching An information specialist (MMM) will develop the search strategies utilizing a combination of subject terms of selected databases and keywords. Search terms will include the concepts of shared decision making and electronic health records. Library colleagues will peer-review the search strategy using the PRESS guidelines (McGowan et al., 2016) Electronic databases will include Medline(Ovid) 1946-2020, Embase (embase.com) 1974 - 2020, CINAHL Complete (Ebscohost) 1937-2020, Cochrane Library (wiley.com) 1898 - 2020 including CENTRAL (wiley.com) 1898-2020, PsycINFO (Ebscohost) 1872-2020, Scopus (scopus.com) 1970-2020 and Web of Science Core Collection (Clarivate Analytics) 1900-2020. No filters will be applied. Online databases will be used to examine published research from 2009-2020. We decided begin our search in 2009 in order to correspond with the adoption of the HITECH Act into law.(Office of the National Coordinator, 2020) Other sources: References of included studies will be checked for relevancy. Study Selection (eligibility criteria) Inclusion criteria o Those patients seeking medical advice from a clinician within a healthcare setting that uses an electronic healthcare system. o Shared decision making tools designed for clinicians and patients for use during a clinical care event. Point of care shared decision making tools that have been integrated into electronic health records. o Various deployment scenario for shared decision making tools including but not limited to single, multiple and extended decision situations. Exclusion criteria o Simulation studies o User design studies o Two reviewers (JP, JB) will independently screen titles and abstracts, then review full texts for inclusion determination. When no consensus can be reached between the two reviewers, a third researcher (CW) will act as a tie breaker and determine the inclusion decision. Inter-rater reliability will be tracked and reported in our manuscript. Analysis of evidence: We intend to perform frequency counts of concepts, populations, and characteristics associated with shared decision making within an EHR. A system of categorization will be developed to categorize the following: o Outcomes by patient, clinician and SDM tool. o Obstacles to effective SDM program adoption. o SDM program features. o SDM treatment settings (eg. Inpatient, office setting, etc.). o Description of the design and implementation for SDM tools and programs. Presentation of results: Results will be presented using narrative descriptions, tables, matrices and charts to convey findings from the scoping review. Specific graph styles will be determined after the data is evaluated. Quality assessment No quality assessment of included studies will be conducted as our goal is to rapidly map the literature. However, we will capture study design, measurement, and statistical elements that are used to measure research quality and bias. Strengths and Limitations Due to time limits, we did not search for grey or unpublished data sources. Another limitation is that our pool of studies came only from published literature indexed by our selected research databases. Charting the data Data extraction will be done with Excel (Microsoft). The principle reviewer (JP) will extract the data and the second reviewer (JB) will check the data. References Alston, C., Z. Berger, S. Brownlee, G. Elwyn, F. J. Fowler Jr., L. K. Hall, V. M. Montori, B. Moulton, L. Paget, B. Haviland-Shebel, R. Singerman, J. Walker, M. K. Wynia, and D. Henderson. (2014). Shared Decision-Making Strategies for Best Care: Patient Decision Aids. NAM Perspectives. . Retrieved from https://nam.edu/perspectives-2014-shared-decision-making-strategies-for-best-carepatient-decision-aids/ Arksey, H., & O'Malley, L. (2005). Scoping studies: towards a methodological framework. International Journal of Social Research Methodology, 8(1), 19-32. doi:10.1080/1364557032000119616 Day, F. C., Pourhomayoun, M., Keeves, D., Lees, A. F., Sarrafzadeh, M., Bell, D., & Pfeffer, M. A. (2019). Feasibility study of an EHR-integrated mobile shared decision making application. Int J Med Inform, 124, 24-30. doi:10.1016/j.ijmedinf.2019.01.008 Legare, F., & Witteman, H. O. (2013). Shared decision making: examining key elements and barriers to adoption into routine clinical practice. Health Aff (Millwood), 32(2), 276-284. doi:10.1377/hlthaff.2012.1078 McGowan, J., Sampson, M., Salzwedel, D. M., Cogo, E., Foerster, V., & Lefebvre, C. (2016). PRESS Peer Review of Electronic Search Strategies: 2015 Guideline Statement. Journal of Clinical Epidemiology, 75, 40-46. doi:https://doi.org/10.1016/j.jclinepi.2016.01.021 Office of the National Coordinator. (2020). Health IT Legislation. Retrieved from https://www.healthit.gov/topic/laws-regulation-and-policy/health-it-legislation Peters MDJ, G. C., McInerney P, Munn Z, Tricco AC, Khalil, H. (2020). Chapter 11: Scoping Reviews (2020 version). JBI Manual for Evidence Synthesis. doi: https://doi.org/10.46658/JBIMES-20-12 Shay, L. A., & Lafata, J. E. (2015). Where is the evidence? A systematic review of shared decision making and patient outcomes. Med Decis Making, 35(1), 114-131. doi:10.1177/0272989X14551638 Tricco, A. C., Lillie, E., Zarin, W., O'Brien, K. K., Colquhoun, H., Levac, D., . . . Straus, S. E. (2018). PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann Intern Med, 169(7), 467-473. doi:10.7326/M18-0850