Literature DB >> 33528233

Health Equity Beyond Data: Health Care Worker Perceptions of Race, Ethnicity, and Language Data Collection in Electronic Health Records.

Taylor M Cruz1, Sheridan A Smith.   

Abstract

BACKGROUND: Recent research and policy initiatives propose addressing the social determinants of health within clinical settings. One such strategy is the expansion of routine data collection on patient Race, Ethnicity, and Language (REAL) within electronic health records (EHRs). Although previous research has examined the general views of providers and patients on REAL data, few studies consider health care workers' perceptions of this data collection directly at the point of care, including how workers understand REAL data in relation to health equity.
OBJECTIVE: This qualitative study examines a large integrated delivery system's implementation of REAL data collection, focusing on health care workers' understanding of REAL and its impact on data's integration within EHRs.
RESULTS: Providers, staff, and administrators expressed apprehension over REAL data collection due to the following: (1) disagreement over data's significance, including the expected purpose of collecting REAL items; (2) perceived barriers to data retrieval, such as the lack of standardization across providers and national tensions over race and immigration; and (3) uncertainty regarding data's use (clinical decision making vs. system research) and dissemination (with whom the data may be shared; eg, public agencies, other providers, and insurers).
CONCLUSION: Emerging racial disparities associated with COVID-19 highlight the high stakes of REAL data collection. However, numerous barriers to health equity remain. Health care workers need greater institutional support for REAL data and related EHR initiatives. Despite data collection's central importance to policy objectives of disparity reduction, data mandates alone may be insufficient for achieving health equity.
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.

Entities:  

Year:  2021        PMID: 33528233     DOI: 10.1097/MLR.0000000000001507

Source DB:  PubMed          Journal:  Med Care        ISSN: 0025-7079            Impact factor:   2.983


  2 in total

1.  Health insurance, healthcare utilization and language use among populations who experience risk for tuberculosis, California 2014-2017.

Authors:  Adam Readhead; Jennifer Flood; Pennan Barry
Journal:  PLoS One       Date:  2022-05-24       Impact factor: 3.752

2.  Missing Race and Ethnicity Data among COVID-19 Cases in Massachusetts.

Authors:  Keith R Spangler; Jonathan I Levy; M Patricia Fabian; Beth M Haley; Fei Carnes; Prasad Patil; Koen Tieskens; R Monina Klevens; Elizabeth A Erdman; T Scott Troppy; Jessica H Leibler; Kevin J Lane
Journal:  J Racial Ethn Health Disparities       Date:  2022-09-02
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.