A Quantitative Bias Analysis Approach to Informative Presence Bias in Electronic Health Records

From the aDepartment of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA

bDivision of Hematology and Oncology, Department of Medicine, University of Pennsylvania, Philadelphia, PA.

Submitted September 8, 2023; accepted January 10, 2024

Research reported in this publication was supported by the National Institute on Aging of the National Institutes of Health under award number R21AG075574.

Disclosures: A.C. has received institutional research support from Lilly and Honoraia from Siemens. R.H. has received funding from Merck. The other author has report no conflicts of interest.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com).

The data that support the findings of the case study in this study have been originated by Flatiron Health, Inc. Requests for data sharing by license or by permission for the specific purpose of replicating results in this manuscript can be submitted to [email protected]. The code to generate the data in the simulation study are available in the supplementary material.

Correspondence: Hanxi Zhang, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, 423 Guardian Dr, 826 Blockley Hall, Philadelphia, PA 19104. E-mail: [email protected].

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