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改善种族、族裔和语言数据收集以减少医疗保健差异:来自一所学术医疗中心的案例研究。

Improving the Collection of Race, Ethnicity, and Language Data to Reduce Healthcare Disparities: A Case Study from an Academic Medical Center.

作者信息

Lee Wei-Chen, Veeranki Sreenivas P, Serag Hani, Eschbach Karl, Smith Kenneth D

机构信息

Center to Eliminate Health Disparities at the University of Texas Medical Branch in Galveston, TX.

Department of Preventive Medicine and Community Health at the University of Texas Medical Branch in Galveston, TX.

出版信息

Perspect Health Inf Manag. 2016 Oct 1;13(Fall):1g. eCollection 2016 fall.

Abstract

Well-designed electronic health records (EHRs) must integrate a variety of accurate information to support efforts to improve quality of care, particularly equity-in-care initiatives. This case study provides insight into the challenges those initiatives may face in collecting accurate race, ethnicity, and language (REAL) information in the EHR. We present the experience of an academic medical center strengthening its EHR for better collection of REAL data with funding from the EHR Incentive Programs for meaningful use of health information technology and the Texas Medicaid 1115 Waiver program. We also present a plan to address some of the challenges that arose during the course of the project. Our experience at an academic medical center can provide guidance about the likely challenges similar institutions may expect when they implement new initiatives to collect REAL data, particularly challenges regarding scope, personnel, and other resource needs.

摘要

设计良好的电子健康记录(EHR)必须整合各种准确信息,以支持提高医疗质量的努力,特别是医疗公平性倡议。本案例研究深入探讨了这些倡议在电子健康记录中收集准确的种族、民族和语言(REAL)信息时可能面临的挑战。我们介绍了一家学术医疗中心在电子健康记录激励计划(用于有意义地使用健康信息技术)和德克萨斯医疗补助1115豁免计划的资助下,加强其电子健康记录以更好地收集REAL数据的经验。我们还提出了一项计划,以应对项目过程中出现的一些挑战。我们在一家学术医疗中心的经验可以为类似机构在实施收集REAL数据的新倡议时可能遇到的挑战提供指导,特别是在范围、人员和其他资源需求方面的挑战。

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