Error codes at autopsy to study potential biases in diagnostic error

Bruce I. Goldman; Rajnish Bharadwaj; Michelle Fuller; Tanzy Love; Leon Metlay; Caroline Dignan

doi:10.1515/dx-2023-0010

Article

Error codes at autopsy to study potential biases in diagnostic error

Bruce I. Goldman , Rajnish Bharadwaj , Michelle Fuller , Tanzy Love , Leon Metlay and Caroline Dignan

Published/Copyright: October 5, 2023

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From the journal Diagnosis Volume 10 Issue 4

Abstract

Objectives

Current autopsy practice guidelines do not provide a mechanism to identify potential causes of diagnostic error (DE). We used our autopsy data registry to ask if gender or race were related to the frequency of diagnostic error found at autopsy.

Methods

Our autopsy reports include International Classification of Diseases (ICD) 9 or ICD 10 diagnostic codes for major diagnoses as well as codes that identify types of error. From 2012 to mid-2015 only 2 codes were used: UNDOC (major undocumented diagnoses) and UNCON (major unconfirmed diagnoses). Major diagnoses contributed to death or would have been treated if known. Since mid-2015, codes included specific diagnoses, i.e. undiagnosed or unconfirmed myocardial infarction, infection, pulmonary thromboembolism, malignancy, or other diagnosis as well as cause of death. Adult autopsy cases from 2012 to 2019 were assessed for DE associated with reported sex or race (nonwhite or white). 528 cases were evaluated between 2012 and 2015 and 699 between 2015 and 2019.

Results

Major DEs were identified at autopsy in 65.9 % of cases from 2012 to 2015 and in 72.1 % from 2015 to 2019. From 2012 to 2015, female autopsy cases showed a greater frequency in 4 parameters of DE, i.e., in the total number of cases with any error (p=0.0001), in the number of cases with UNDOC errors (p=0.0038) or UNCON errors (p=0.0006), and in the relative proportions of total numbers of errors (p=0.0001). From 2015 to 2019 undocumented malignancy was greater among males (p=0.0065); no other sex-related error was identified. In the same period some DE parameters were greater among nonwhite than among white subjects, including unconfirmed cause of death (p=0.035), and proportion of total error diagnoses (p=0.0003), UNCON diagnoses (p=0.0093), and UNDOC diagnoses (p=0.035).

Conclusions

Coding for DE at autopsy can identify potential effects of biases on diagnostic error.

Keywords: autopsy; International Classification of Diseases; registries; diagnostic error

Corresponding author: Bruce I. Goldman, MD, Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave. box 626, Rochester, NY 14642, USA, Phone: +1 (585) 273 3401, Fax: +1 (585) 273 1027, E-mail: Bruce_Goldman@URMC.Rochester.edu.

Acknowledgments

The authors thank Tracy Baird of the Office of Clinical Practice Evaluation (OCPE) and David Pinto of the Clinical and Translational Science Institute (CTSI) for assisting in obtaining demographic and diagnostic coding data from the electronic medical record.

Research ethics: This study was was in compliance with HIPAA requirements and exempt from the Institutional Research Subjects Review Board (RSRB) approval because decedents are not considered individuals according to the Federal definition of research subjects.
Informed consent: Not appliable.
Author contributions: Dr. Goldman was responsible for study design and data analysis. Dr. Love provided assistance with statistical methods. Drs. Bharadwaj, Love, Metlay, and Dignan contributed primary coding data, manuscript review, and helpful discussion. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
Competing interests: TThe authors state no conflict of interest.
Research funding: This project was supported by the Department of Pathology and Laboratory Medicine at the University of Rochester and received no grant funding or external financial support.
Data availability: The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

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Received: 2023-01-26

Accepted: 2023-08-20

Published Online: 2023-10-05

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Articles in the same Issue

https://doi.org/10.1515/dx-2023-0010

Keywords for this article

autopsy; International Classification of Diseases; registries; diagnostic error