Normalization of a conversation tool to promote shared decision making about anticoagulation in patients with atrial fibrillation within a practical randomized trial of its effectiveness: a cross-sectional study
Open accessAbstract
Background: Shared decision making (SDM) implementation remains challenging. The factors that promote or hinder implementation of SDM tools for use during the consultation, including contextual factors such as clinician burnout and organizational support, remain unclear. We explored these factors in the context of a practical multicenter randomized trial evaluating the effectiveness of an SDM conversation tool for patients with atrial fibrillation considering anticoagulation therapy. Methods: In this cross-sectional study, we recruited clinicians who were regularly involved in conversations with patients regarding anticoagulation for atrial fibrillation. Clinicians reported their characteristics and burnout symptoms using the two-item Maslach Burnout Inventory. Clinicians were trained in using the SDM tool, and they recorded their perceptions of the tool’s normalization potential using the Normalization MeAsure Development (NoMAD) survey instrument and verbally reflected on their answers to these survey questions. When possible, the training sessions and clinicians’ verbal responses to the conversation tool were recorded. Results: Our study comprised 183 clinicians recruited into the trial (168 with survey responses and 112 with recordings). Overall, clinicians gave high scores to the normalization potential of the intervention; they endorsed all domains of normalization to the same extent, regardless of site, clinician characteristics, or burnout ratings. In interviews, clinicians paid significant attention to making sense of the tool. Tool buy-in seemed to depend heavily on their ability to see the tool as accurate and “evidence-based” and their perceptions of having time in the consultation to use it. Conclusions: While time in the consultation remains a barrier, we did not find a significant association between burnout symptoms and normalization of an SDM conversation tool. Possible areas for improving the normalization of SDM conversation tools in clinical practice include enabling collaboration among clinicians to implement the tool and reporting how clinicians elsewhere use the tool. Direct measures of normalization (i.e., observing how often clinicians access the tool in practice outside of the clinical trial) may further elucidate the role that contextual factors, such as clinician burnout, play in the implementation of SDM. Trial registration: ClinicalTrials.gov, NCT02905032. Registered on 9 September 2016.
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May, C. R., Mair, F., Finch, T., MacFarlane, A., Dowrick, C., Treweek, S., Rapley, T., Ballini, L., Ong, B. N., Rogers, A., et al. (2009) · Implementation Science · doi:10.1186/1748-5908-4-29 · Cited by 1,409 · see citing works
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Oakley, A., Strange, V., Bonell, C., Allen, E., & Stephenson, J. (2006) · BMJ · doi:10.1136/bmj.332.7538.413 · Cited by 1,247 · see citing works
Légaré, F., & Witteman, H. O. (2013) · Health Affairs · doi:10.1377/hlthaff.2012.1078 · Cited by 783 · see citing works
Thomas, N. K. (2004) · JAMA · doi:10.1001/jama.292.23.2880 · Cited by 750 · see citing works
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West, C. P., Dyrbye, L. N., Satele, D., Sloan, J. A., & Shanafelt, T. D. (2012) · Journal of General Internal Medicine · doi:10.1007/s11606-012-2015-7 · Cited by 525 · see citing works
A systematic review of the reliability of objective structured clinical examination scores
Brannick, M. T., Erol‐Korkmaz, H. T., & Prewett, M. (2011) · Medical Education · doi:10.1111/j.1365-2923.2011.04075.x · Cited by 354 · see citing works
Finch, T. L., Girling, M., May, C. R., Mair, F. S., Murray, E., Treweek, S., McColl, E., Steen, I. N., Cook, C., Vernazza, C. R., et al. (2018) · BMC Medical Research Methodology · doi:10.1186/s12874-018-0591-x · Cited by 337 · see citing works
Self-citationLamothe, M., Boujut, É., Zenasni, F., & Sultan, S. (2014) · BMC Family Practice · doi:10.1186/1471-2296-15-15 · Cited by 291 · see citing works
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Xuereb, C. B., Shaw, R. L., & Lane, D. A. (2012) · Patient Education and Counseling · doi:10.1016/j.pec.2012.05.011 · Cited by 66 · see citing works
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Self-citationHuynh, C., Bowles, D., Yen, M.-S., Phillips, A., Waller, R., Hall, L., & Tu, S.-P. (2018) · Journal of Interprofessional Care · doi:10.1080/13561820.2018.1451307 · Cited by 17 · see citing works
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- Authors
- Shared Decision Making for Atrial Fibrillation (SDM4AFib) Trial Investigators, Spencer-Bonilla, G., Thota, A., Organick, P., Ponce, O. J., Kunneman, M., Giblon, R., Branda, M. E., Sivly, A. L., Behnken, E., May, C. R., & Montori, V. M.
- Affiliations
- Mayo Clinic (US)
- ORCID
- Venue
- Trials
- Published
- 2020-05-12
- Volume
- 21
- Issue
- 1
- Pages
- 395-395
- ISSN
- 1745-6215 (ISSN-L)
- PMC
- PMC7218532
- OpenAlex
- W3024802804
- Cited by
- 17
- References
- 23
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 1 · 2023: 4 · 2022: 4 · 2021: 1 · 2020: 1
- FWCI
- 2.61
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Trials (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Leiden Repository (Leiden University) (submittedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Heart, Lung, and Blood Institute (R01HL131535, R01HL131535-01S1)
- National Center for Advancing Translational Sciences (UL1TR000135)
- Topics
- Health Sciences › Health Professions › General Health Professions › Health Policy Implementation Science
- Health Sciences › Health Professions › General Health Professions › Patient-Provider Communication in Healthcare
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
- Keywords
- shared decision-making, atrial fibrillation, anticoagulation, conversation tool, clinician burnout, implementation barriers, clinician perceptions, consultation time, clinician training
- MeSH terms
- Burnout, Psychological, Decision Making, Shared, Adult, Anticoagulants, Atrial Fibrillation, Communication, Cross-Sectional Studies, Decision Support Techniques, Female, Health Personnel, Humans, Male, Middle Aged, Patient Participation, Surveys and Questionnaires, Referral and Consultation, Social Theory
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