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Factors Associated With Diagnostic Error: An Analysis of Closed Medical Malpractice Claims.
Journal of Patient Safety 2023 January 13
INTRODUCTION: Missed and delayed diagnoses have received substantial attention as a quality and patient safety priority. To the extent that electronic health records, team-based care, and other mitigation strategies have been successful in improving diagnosis since the last large-scale study, we would expect that the contributing factors to diagnostic claims may have changed.
METHODS: This study sought to examine paid medical malpractice claims as a proxy to identify contributing factors that reflect a clear diagnostic error. Diagnostic error cases with indemnity payments (2009-2020) were identified using the Candello (formerly known as CRICO) proprietary taxonomy. Factors associated with indemnity payments were analyzed using a multivariable logistic regression model.
RESULTS: Of 5367 included claims, 2161 (40%) had indemnity payments. A majority of claims had multiple contributing factors on the diagnostic pathway. In multivariable analysis, factors independently associated with an indemnity payment included the insurer (odds ratio and 95% confidence interval, 2.8 [2.4-3.3]), high injury severity (1.9 [1.3-2.8]) or death (1.5 [0.99-2.1]), and case setting (inpatient (0.77 [0.65-0.91]) or emergency department (0.67 [0.49-0.92])). Importantly, cases with contributing factors outside of Candello's diagnostic pathway were more likely to lead to indemnity payment.
CONCLUSIONS: The digital transformation and acceleration of team-based care in medicine have not mitigated the malpractice risks of complex cases with severe injuries and multiple missteps.
METHODS: This study sought to examine paid medical malpractice claims as a proxy to identify contributing factors that reflect a clear diagnostic error. Diagnostic error cases with indemnity payments (2009-2020) were identified using the Candello (formerly known as CRICO) proprietary taxonomy. Factors associated with indemnity payments were analyzed using a multivariable logistic regression model.
RESULTS: Of 5367 included claims, 2161 (40%) had indemnity payments. A majority of claims had multiple contributing factors on the diagnostic pathway. In multivariable analysis, factors independently associated with an indemnity payment included the insurer (odds ratio and 95% confidence interval, 2.8 [2.4-3.3]), high injury severity (1.9 [1.3-2.8]) or death (1.5 [0.99-2.1]), and case setting (inpatient (0.77 [0.65-0.91]) or emergency department (0.67 [0.49-0.92])). Importantly, cases with contributing factors outside of Candello's diagnostic pathway were more likely to lead to indemnity payment.
CONCLUSIONS: The digital transformation and acceleration of team-based care in medicine have not mitigated the malpractice risks of complex cases with severe injuries and multiple missteps.
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