Thursday, November 21, 2024
11/21/2024
PROJECT SUMMARY The diagnostic process is an iterative, time-dependent, and collaborative decision-making process under uncertainty to reach an explanation for the patient’s health condition(s) and communicate this explanation to the patient. Appropriate healthcare delivery depends on the proximity between a patient’s health condition and diagnosis and yet, diagnostic errors remain a leading cause of morbidity and mortality in the U.S. Considering the volume and variety of primary care patients, combined with the practical challenges of scarce and costly referral and testing resources, the incidence of diagnostic errors can disproportionally affect medically underserved and vulnerable patient populations. Diagnostic disparities occur when preventable diagnostic errors are experienced disproportionately among certain patient demographic subgroups. Research has shown disparities in diagnostic error s by race and ethnicity, sex, gender, geographic location, and socioeconomic status, in part due to implicit bias, discrimination, and stigma. However, the relationship between diagnostic equity (i.e., diagnostic disparities related to diagnostic error due to systemic challenges in policies and practices) and diagnostic uncertainty (i.e., subjective perception of an inability to provide an accurate explanation of the patient's health problem) is poorly understood. Diagnostic uncertainty, a concept that has yet to be adequately operationalized in medical practice, is a natural part of medicine and more common in primary care than any other specialty. Identification of indicators and causes for diagnostic errors is crucial to avoid patient harm. Previous studies linked diagnostic uncertainty to diagnostic variation (i.e., physicians providing different diagnosis for the same patient), over-testing, increased hospitalization, and referrals. Yet, the connection between diagnostic uncertainty and diagnostic equity remains an understudied domain. While there is an increasing need to develop data-driven and evidence-based methods to study the relationship between diagnostic equity and diagnostic uncertainty, the complexity, time dependency, and uncertainty of the diagnostic process makes this challenging. Therefore, we have developed the Improving Diagnostic Equity in Ambulatory care Settings (I.D.E.A.S.): Research to Practice study to evaluate diagnostic errors in the context of diagnostic equity and diagnostic uncertainty through the application of decision-modeling and human factors methodologies. The novelty of the proposed study lies in its unique interdisciplinary approach, bringing together clinical diagnostician expertise, data science, operations research, and human factors engineering, to work towards methodological advances in conceptualizing and measuring diagnostic errors. Expected outcomes will lay the foundation for designing a comprehensive framework via an equity lens to connect diagnostic equity and diagnostic uncertainty to inform interventions aimed at reducing diagnostic inequity and improving the management of diagnostic uncertainty.
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