Navigating electronic health record accuracy by examination of sex incongruent conditions.

Autor:	Cai L; Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Children's Research Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States., DeBerardinis RJ; Children's Research Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States., Zhan X; Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Center for Genetics of Host Defense, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States., Xiao G; Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States., Xie Y; Quantitative Biomedical Research Center, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.; Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, TX 75390, United States.
Jazyk:	angličtina
Zdroj:	Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2024 Dec 01; Vol. 31 (12), pp. 2849-2856.
DOI:	10.1093/jamia/ocae236
Abstrakt:	Objective: The increasing reliance on electronic health records (EHRs) for research and clinical care necessitates robust methods for assessing data quality and identifying inconsistencies. To address this need, we develop and apply the incongruence rate (IR) using sex-specific medical conditions. We also characterized participants with incongruent records to better understand the scope and nature of data discrepancies. Materials and Methods: In this cross-sectional study, we used the All of Us Research Program's latest version 7 (v7) EHR data to identify prevalent sex-specific conditions and evaluated the occurrence of incongruent cases, quantified as IR. Results: Among the 92 597 males and 152 551 females with condition occurrence data available from All of Us and sex-conformed gender, we identified 167 prevalent sex-specific conditions. Among the 37 537 biological males and 95 499 biological females with these sex-specific conditions, we detected an overall IR of 0.86%. Attempt to include non-cisgender participants result in inflated overall IR. Additionally, a significant proportion of participants with incongruent conditions also presented with conditions congruent to their biological sex, indicating a mix of accurate and erroneous records. These incongruences were not geographically or temporally isolated, suggesting systematic issues in EHR data integrity. Discussion: Our findings call attention to the existence of systemic data incongruences in sex-specific conditions and the need for robust validation checks. Extending IR evaluation to non-cisgender participants or non-sex-based conditions remain a challenge. Conclusion: The sex condition-specific IR, when applied to adult populations, provides a valuable metric for data quality assessment in EHRs. (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association.)
Databáze:	MEDLINE
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