Controlling for Informed Presence Bias Due to the Number of Health Encounters in an Electronic Health Record.

Published

Journal Article

Electronic health records (EHRs) are an increasingly utilized resource for clinical research. While their size allows for many analytical opportunities, as with most observational data there is also the potential for bias. One of the key sources of bias in EHRs is what we term informed presence-the notion that inclusion in an EHR is not random but rather indicates that the subject is ill, making people in EHRs systematically different from those not in EHRs. In this article, we use simulated and empirical data to illustrate the conditions under which such bias can arise and how conditioning on the number of health-care encounters can be one way to remove this bias. In doing so, we also show when such an approach can impart M bias, or bias from conditioning on a collider. Finally, we explore the conditions under which number of medical encounters can serve as a proxy for general health. We apply these methods to an EHR data set from a university medical center covering the years 2007-2013.

Full Text

Duke Authors

Cited Authors

  • Goldstein, BA; Bhavsar, NA; Phelan, M; Pencina, MJ

Published Date

  • December 2016

Published In

Volume / Issue

  • 184 / 11

Start / End Page

  • 847 - 855

PubMed ID

  • 27852603

Pubmed Central ID

  • 27852603

Electronic International Standard Serial Number (EISSN)

  • 1476-6256

International Standard Serial Number (ISSN)

  • 0002-9262

Digital Object Identifier (DOI)

  • 10.1093/aje/kww112

Language

  • eng