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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...
Autores principales: | Goldstein, Neal D., Kahal, Deborah, Testa, Karla, Gracely, Ed J., Burstyn, Igor |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
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 |
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