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Uncertainty in Decision Making in Medicine: A Scoping Review and Thematic Analysis of Conceptual Models
Marieka A Helou1, Deborah DiazGranados, Michael S Ryan
1M.A. Helou is assistant professor, Department of Pediatrics, Virginia Commonwealth University School of Medicine, Richmond, Virginia; ORCID: https://orcid.org/0000-0002-8650-5901. D. DiazGranados is assistant professor, Virginia Commonwealth University School of Medicine, Richmond, Virginia; ORCID: https://orcid.org/0000-0002-0624-7093. M.S. Ryan is associate professor, Department of Pediatrics, and assistant dean for clinical medical education, Virginia Commonwealth University School of Medicine, Richmond, Virginia; ORCID: https://orcid.org/0000-0003-3266-9289. J.W. Cyrus is assistant professor, Tompkins-McCaw Library for the Health Sciences, Virginia Commonwealth University School of Medicine, Richmond, Virginia; ORCID: https://orcid.org/0000-0001-5331-5151.
Purpose:
The practice of medicine is rarely straightforward. Data used to facilitate medical decision making may be conflicting, ambiguous, or scarce, and providing optimal care requires balancing clinicians' expertise and available evidence with patients' preferences. To explore uncertainty in decision making across disciplines, the authors performed a scoping review and thematic analysis of the literature to formulate a model describing the decision-making process in medicine under uncertain conditions.
Method:
In 2016, the authors performed a comprehensive search of key databases using a combination of keywords and controlled vocabulary. They identified and reviewed 3,398 records. After applying their inclusion and exclusion criteria to the titles and abstracts and then full texts, 19 articles were selected. The authors applied a qualitative thematic analysis to these articles, using codes to extract themes related to uncertainty in decision making.
Results:
The 19 articles spanned 6 fields of study and 5 disciplines within the health sciences. The thematic analysis revealed 6 main themes: recognition of uncertainty, classification of uncertainty, stakeholder perspectives, knowledge acquisition, decision-making approach, and evaluation of the decision-making process.
Conclusions:
Based on the themes that emerged from their thematic analysis of the literature characterizing the effects of uncertainty and ambiguity on the decision-making process, the authors developed a framework depicting the interplay between these themes with a visual representation of the decision-making process under uncertain conditions. Future research includes further development and validation of this framework to inform medical school curricula.
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