Problem Definition: Diagnostic discrepancies, defined as mismatches between patients’ admitting and principal diagnoses, are common but heterogeneous claims-based markers. These discrepancies represent a misalignment in the diagnostic process, reflecting diagnostic updating, reprioritization, residual clinical complexity, documentation practices, or error, without establishing clinical preventability, and may signal latent operational burden in subsequent physician decision-making. We examine whether this retrospective operational flag identifies inpatient stays with larger adjusted resource-use differentials and whether those differentials vary with physician experience. Methodology/Results: Leveraging a patient-level dataset of 5.7 million emergency-department-origin inpatient stays from Florida hospitals, we examine the operational burden associated with diagnostic discrepancies, measured by total costs per hospitalization. Our results show that discrepancy-flagged inpatient stays have a 6.62% higher adjusted total cost after rich patient risk adjustment and high-dimensional fixed effects. The adjusted differential is smaller at higher focal experience (treating similar diagnoses) and larger at higher related experience (treating diverse diagnoses). The pattern remains qualitatively similar across alternative discrepancy definitions, richer diagnosis and service-line controls, risk-adjusted benchmarking, physician matching, alternative experience measures, and alternative samples. Exploratory analyses further show that flagged inpatient stays exhibit higher costs across multiple resource-use domains with varying intensity, higher diagnostic and procedural intensity, and longer adjusted time to first procedure. Managerial Implications: The discrepancy flag is most appropriately used for retrospective monitoring, benchmarking, and case-review triage, not as a direct measure of preventable error or as an automatic performance score. The physician experience patterns motivate prospective evaluation of assignment, consultation, training, and decision-support practices.
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Youn et al. (2026) studied this question.
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