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Licensed Unlicensed Requires Authentication Published by De Gruyter July 24, 2020

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

  • Adam L. Sharp EMAIL logo , Aileen Baecker , Najlla Nassery , Stacy Park , Ahmed Hassoon , Ming-Sum Lee , Susan Peterson , Samantha Pitts , Zheyu Wang , Yuxin Zhu and David E. Newman-Toker
From the journal Diagnosis

Abstract

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.


Corresponding author: Adam L. Sharp, MD, MSc, Department of Research and Evaluation, Kaiser Permanente Southern California, 100 S Los Robles Avenue, 2nd Floor, Pasadena, CA, 91101, United States, and Department of Health System Science, Kaiser Permanente School of Medicine, Pasadena, CA, United States, Phone: +626 564 3965, Fax: +626-564-3694, E-mail:

Award Identifier / Grant number: GBMF5756

Acknowledgments

The authors thank Visanee Musigdilok for her administrative assistance with this project and the patients of Kaiser Permanente for helping us improve care using information collected via our electronic health record systems.

  1. Research funding: This work was funded by a grant from the Gordon & Betty Moore Foundation (GBMF5756). Dr. Newman-Toker’s effort was supported partly by the Armstrong Institute Center for Diagnostic Excellence at the Johns Hopkins University School of Medicine.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Dr. Newman-Toker conducts research related to diagnostic error, including serving as the principal investigator for grants on this topic. He serves as an unpaid member of the Board of Directors of the Society to Improve Diagnosis in Medicine and as its current President. He serves as a medico-legal consultant for both plaintiff and defense in cases related to diagnostic error. There are no other conflicts of interest. None of the authors have any financial or personal relationships with other people or organizations that could inappropriately influence (bias) their work.

  4. Ethical approval: This study was approved by the Kaiser Permanente Southern California Institutional Review Board.

Appendix ICD-9-CM, and ICD-10-CM codes used for acute myocardial infarction (AMI)

AMI ICD-9-CM Codes: 410.00, 410.0, 1410.01, 410.02, 410.10, 410.11, 410.11, 410.11, 410.11, 410.12, 410.20, 410.21, 410.21, 410.22, 410.30, 410.31, 410.31, 410.32, 410.40, 410.41, 410.41, 410.42, 410.50, 410.51, 410.51, 410.52, 410.60, 410.61, 410.61, 410.62, 410.70, 410.71, 410.71, 410.72, 410.80, 410.81, 410.81, 410.81, 410.82, 410.90, 410.91, 410.91, 410.92

AMI ICD-10-CM Codes: I21, I22

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Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/dx-2020-0049).


Received: 2020-04-17
Accepted: 2020-06-03
Published Online: 2020-07-24
Published in Print: 2021-05-26

© 2020 Walter de Gruyter GmbH, Berlin/Boston

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