Data Quality in Electronic Health Record Research: An Approach for Validation and Quantitative Bias Analysis for Imperfectly Ascertained Health Outcomes Via Diagnostic Codes-Reference-Cited by-同舟云学术

Data Quality in Electronic Health Record Research: An Approach for Validation and Quantitative Bias Analysis for Imperfectly Ascertained Health Outcomes Via Diagnostic Codes

Published:2022-04-28 Issue: Volume: Page:
ISSN:
Container-title:Harvard Data Science Review
language:en
Short-container-title:

Author:

Goldstein Neal D.¹,Kahal Deborah²,Testa Karla³,Gracely Ed J.⁴,Burstyn Igor⁵

Affiliation:

1. Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, United States of America

2. William J. Holloway Community Program, ChristianaCare, Wilmington, Delaware, United States of America; Sydney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America

3. Sydney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America; Westside Family Healthcare, Wilmington, Delaware, United States of America

4. Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, United States of America; Department of Family, Community, and Preventive Medicine, College of Medicine, Drexel University, Philadelphia, Pennsylvania, United States of America

5. Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, United States of America; Department of Environmental and Occupational Health, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, United States of America

Publisher

MIT Press - Journals

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2. Design, implementation, and inferential issues associated with clinical trials that rely on data in electronic medical records: a narrative review;BMC Medical Research Methodology;2023-11-16

3. Biases in Electronic Health Records Data for Generating Real-World Evidence: An Overview;Journal of Healthcare Informatics Research;2023-11-14

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