Objectives: Diagnostic error is a serious public health problem. Measuring diagnostic performance remains elusive. We sought to measure misdiagnosis-related harms following missed acute myocardial infarctions (AMI) in the emergency department (ED) using the symptom-disease pair analysis of diagnostic error (SPADE) method.
Methods: Retrospective administrative data analysis (2009-2017) from a single, integrated health system using International Classification of Diseases (ICD) coded discharge diagnoses. We looked back 30 days from AMI hospitalizations for antecedent ED treat-and-release visits to identify symptoms linked to probable missed AMI (observed > expected). We then looked forward from these ED discharge diagnoses to identify symptom-disease pair misdiagnosis-related harms (AMI hospitalizations within 30-days, representing diagnostic adverse events).
Results: A total of 44,473 AMI hospitalizations were associated with 2,874 treat-and-release ED visits in the prior 30 days. The top plausibly-related ED discharge diagnoses were "chest pain" and "dyspnea" with excess treat-and-release visit rates of 9.8% (95% CI 8.5-11.2%) and 3.4% (95% CI 2.7-4.2%), respectively. These represented 574 probable missed AMIs resulting in hospitalization (adverse event rate per AMI 1.3%, 95% CI 1.2-1.4%). Looking forward, 325,088 chest pain or dyspnea ED discharges were followed by 508 AMI hospitalizations (adverse event rate per symptom discharge 0.2%, 95% CI 0.1-0.2%).
Conclusions: The SPADE method precisely quantifies misdiagnosis-related harms from missed AMIs using administrative data. This approach could facilitate future assessment of diagnostic performance across health systems. These results correspond to ∼10,000 potentially-preventable harms annually in the US. However, relatively low error and adverse event rates may pose challenges to reducing harms for this ED symptom-disease pair.
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http://dx.doi.org/10.1515/dx-2020-0049 | DOI Listing |
Diagnosis (Berl)
December 2024
Department of Pediatrics, University of Utah School of Medicine, Salt Lake City, UT, USA.
Diagnosis (Berl)
August 2024
Neurology, 1501 Johns Hopkins Medicine , Baltimore, MD, USA.
Objectives: Diagnostic errors are the leading cause of preventable harm in clinical practice. Implementable tools to quantify and target this problem are needed. To address this gap, we aimed to generalize the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) framework by developing its computable phenotype and then demonstrated how that schema could be applied in multiple clinical contexts.
View Article and Find Full Text PDFBMJ Qual Saf
January 2024
Candello, The Risk Management Foundation of the Harvard Medical Institutions Inc, Boston, Massachusetts, USA.
Background: Diagnostic errors cause substantial preventable harms worldwide, but rigorous estimates for total burden are lacking. We previously estimated diagnostic error and serious harm rates for key dangerous diseases in major disease categories and validated plausible ranges using clinical experts.
Objective: We sought to estimate the annual US burden of serious misdiagnosis-related harms (permanent morbidity, mortality) by combining prior results with rigorous estimates of disease incidence.
Diagnosis (Berl)
August 2023
Department of Neurology and the Armstrong Institute Center for Diagnostic Excellence, The Johns Hopkins University School of Medicine, Baltimore, USA.
Diagnostic errors in medicine represent a significant public health problem but continue to be challenging to measure accurately, reliably, and efficiently. The recently developed Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach measures misdiagnosis related harms using electronic health records or administrative claims data. The approach is clinically valid, methodologically sound, statistically robust, and operationally viable without the requirement for manual chart review.
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