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Real-World Data for Interdisciplinary Health Care Research: A Case Example.
Nahm, Eun-Shim; Zhu, Shijun; Seidl, Kristin; Chen, Lynn; Day, Jenni; Seong, Hohyun.
Afiliação
  • Nahm ES; Department of Organizational Systems and Adult Health, University of Maryland School of Nursing, Baltimore (Drs Nahm, Zhu, and Chen); and Department of Quality and Safety (Dr Seidl) and Director of Nursing Inquiry (Dr day), University of Maryland Medical Center, Baltimore. Mr Seong is a doctoral student at University of Maryland School of Nursing, Baltimore.
ANS Adv Nurs Sci ; 46(4): 349-362, 2023.
Article em En | MEDLINE | ID: mdl-37102714
ABSTRACT
Real-word data (RWD) refer to data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources, including electronic health records, medical claims data, and patient-generated data. Data sets that combine personal health data stored in different sources can provide a more complete picture of an individual's health and can be used to improve population health through research and practice. The 2-tiered aim of this article is to provide a brief introduction to using RWD in health care research and to present a case study that demonstrates data curation and data merge from different sources while highlighting the benefits and limitations of using RWD. The current digital health ecosystem and value-based care approach highlight the need to use RWD to catalyze the advancement of health care research and practice. This is an excellent field that nurse researchers can lead, as they have an innate understanding of such data and data sources.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Atenção à Saúde Aspecto: Patient_preference Limite: Humans Idioma: En Revista: ANS Adv Nurs Sci Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Atenção à Saúde Aspecto: Patient_preference Limite: Humans Idioma: En Revista: ANS Adv Nurs Sci Ano de publicação: 2023 Tipo de documento: Article