Missed acute myocardial infarction in the emergency department-standardizing measurement of misdiagnosis-related harms using the SPADE method.

chest pain diagnostic errors dyspnea emergency medical services health services research healthcare disparities myocardial infarction

Journal

Diagnosis (Berlin, Germany)
ISSN: 2194-802X
Titre abrégé: Diagnosis (Berl)
Pays: Germany
ID NLM: 101654734

Informations de publication

Date de publication:
26 05 2021
Historique:
received: 17 04 2020
accepted: 03 06 2020
pubmed: 24 7 2020
medline: 16 10 2021
entrez: 24 7 2020
Statut: epublish

Résumé

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. 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). 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%). 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.

Identifiants

pubmed: 32701479
doi: 10.1515/dx-2020-0049
pii: dx-2020-0049
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

177-186

Informations de copyright

© 2020 Walter de Gruyter GmbH, Berlin/Boston.

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Auteurs

Adam L Sharp (AL)

Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.
Department of Health System Science, Kaiser Permanente School of Medicine, Pasadena, CA, United States.

Aileen Baecker (A)

Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.

Najlla Nassery (N)

Department of Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.

Stacy Park (S)

Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, United States.

Ahmed Hassoon (A)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.

Ming-Sum Lee (MS)

Kaiser Permanente Southern California, Los Angeles Medical Center, Division of Cardiology, Los Angeles, CA, United States.

Susan Peterson (S)

Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.

Samantha Pitts (S)

Department of Internal Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.

Zheyu Wang (Z)

Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.

Yuxin Zhu (Y)

Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.

David E Newman-Toker (DE)

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.
Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, United States.

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