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Implicit and Explicit Factors That Influence Surgeons' Decision-Making for Distal Radius Fractures in Older Patients. | LitMetric

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Article Abstract

Purpose: The purpose of this study was to evaluate factors that influence surgeons' decision-making in the treatment of distal radius fractures in older patients.

Methods: Fourteen clinical vignettes of a 72-year-old patient with a distal radius fracture were sent to 185 orthopedic hand and/or trauma surgeons. The surgeons were surveyed regarding the demographic/practice details, treatment decision (surgical or nonsurgical), and factors that influenced management, including the Charlson Comorbidity Index, functional status, radiographic appearance, and handedness. Multivariable regression analyses were used to assess the effect of both surgeon-described (explicit) and given clinical (implicit) factors on the treatment decision and to evaluate for discrepancies.

Results: Sixty-six surgeons completed the survey, and 7 surgeons completed 10-13 vignettes. Surgeons made the explicit determination to pursue nonsurgical treatment based on the presence of comorbidities (odds ratio [OR], 0.02 for surgery; 95% confidence interval [CI], 0.01-0.05), but the observation of the underlying clinical data suggested that the recommendation for surgical treatment was instead based on a higher functional status (OR, 3.54/increase in functional status; 95% CI, 2.52-4.98). Those employed by hospitals/health systems were significantly less likely to recommend surgery than those in private practice (OR, 0.42; 95% CI, 0.23-0.79) CONCLUSIONS: This study demonstrates that the presence of comorbidities, functional status, and practice setting has a significant impact on a surgeon's decision to treat distal radius fractures in older patients. The discrepancy between the surgeon-described factors and underlying clinical data demonstrates cognitive bias.

Clinical Relevance: Surgeons should be aware of cognitive biases in clinical reasoning and should work through consequential patient decisions using an analytical framework that attempts to reconcile all available clinical data.

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http://dx.doi.org/10.1016/j.jhsa.2022.03.013DOI Listing

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