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

It is incumbent upon all researchers who use the electronic health record (EHR), including data scientists, to understand the quality of such data. EHR data may be subject to measurement error or misclassification that have the potential to bias results, unless one applies the available computationa...

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Detalles Bibliográficos
Autores principales: Goldstein, Neal D., Kahal, Deborah, Testa, Karla, Gracely, Ed J., Burstyn, Igor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9624477/
https://www.ncbi.nlm.nih.gov/pubmed/36324333
http://dx.doi.org/10.1162/99608f92.cbe67e91

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9624477/
https://www.ncbi.nlm.nih.gov/pubmed/36324333
http://dx.doi.org/10.1162/99608f92.cbe67e91

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