Hadi Amiri, Nidhi Vakil, Mohamed Elgaar, Jiali Cheng, Mitra Mohtarami, Adrian Wong, Mehrnaz Sadrolashrafi, Leo Anthony G. Celi
{"title":"Analysis of Race, Sex, and Language Proficiency Disparities in Documented Medical Decisions","authors":"Hadi Amiri, Nidhi Vakil, Mohamed Elgaar, Jiali Cheng, Mitra Mohtarami, Adrian Wong, Mehrnaz Sadrolashrafi, Leo Anthony G. Celi","doi":"10.1101/2024.07.11.24310289","DOIUrl":null,"url":null,"abstract":"Abstract\nImportance: 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.","PeriodicalId":501454,"journal":{"name":"medRxiv - Health Informatics","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.07.11.24310289","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract
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.