Analysis of Race, Sex, and Language Proficiency Disparities in Documented Medical Decisions

Abstract

Question Are there disparities associated with race, sex, or language proficiency of patients in documented medical decisions within discharge summaries?

Finding This study included expert annotation of 56,759 medical decisions across 451 discharge summaries reveals significant disparities associated with language proficiency of patients across different types of medical decisions in discharge summaries of specific disease groups.

Meaning Disparities associated with sex and language proficiency of patients are present in the documentation of medical decisions, and addressing such disparities might promote equitable care and prevent computational models from learning and perpetuating such biases.

Importance Detecting potential disparities in documented medical decisions is a crucial step toward achieving more equitable practices and care, informing healthcare policy making, and preventing computational models from learning and perpetuating such biases.

Objective To identify disparities associated with race, sex and language proficiency of patients in the documentation of medical decisions.

Design This cross-sectional study included 451 discharge summaries from MIMIC-III, with all medical decisions annotated by domain experts according to the 10 medical decision categories defined in the Decision Identification and Classification Taxonomy for Use in Medicine. Annotated discharge summaries were stratified by race, sex, language proficiency, diagnosis codes, type of ICU, patient status code, and patient comorbidities (quantified by Elixhauser Comorbidity Index) to account for potential confounding factors. Welch’s t-test with Bonferroni correction was used to identify significant disparities in the frequency of medical decisions.

Setting The study used the MIMIC-III data set, which contains de-identified health data for patients admitted to the critical care units at the Beth Israel Deaconess Medical Center.

Participants The population reflects the race, sex, and clinical conditions of patients in a data set developed by previous work for patient phenotyping.

Main Outcomes and Measures The primary outcomes were different types of disparities associated with language proficiency of patients in documented medical decisions within discharge summaries, and the secondary outcome was the prevalence of medical decisions documented in discharge summaries. The data set will be made available at https://physionet.org/

Results This study analyzed 56,759 medical decision text segments documented in 451 discharge summaries. Analysis across demographic groups revealed a higher documentation frequency for English proficient patients compared to non-English proficient patients in several categories, suggesting potential disparities in documentation or care. Specifically, English proficient patients consistently had more documented decisions in critical decision categories such as “Defining Problem” in conditions related to circulatory system and endocrine, nutritional and metabolic diseases. However, this study found no significant disparities in medical decision documentation based on sex or race.

Conclusions and Relevance This study illustrates disparities in the documentation of medical decisions, with English proficient patients receiving more comprehensive documentation compared to non-English proficient patients. Conversely, no significant disparity was identified in terms of sex or race. These findings suggest a potential need for targeted interventions to improve the equity of medical documentation practices so that all patients receive the same level of detailed care documentation and prevent computational models from learning and perpetuating such biases.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This study did not receive any external funding.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Ethics committee/IRB of "The PhysioNet Team, Massachusetts Institute of Technology Laboratory for Computational Physiology Institute for Medical Engineering and Science" gave ethical approval for this work.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

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