Learning About Missing Data Mechanisms in Electronic Health Records-based Research: A Survey-based Approach.

ABSTRACT:

Background

Bias due to missing data is a major concern in electronic health record (EHR)-based research. As part of an ongoing EHR-based study of weight change among patients treated for depression, we conducted a survey to investigate determinants of missingness in the available weight information and to evaluate the missing-at-random assumption.

Methods

We identified 8,345 individuals enrolled in a large EHR-based health care system who had monotherapy treatment for depression from April 2008 to March 2010. A stratified sample of 1,153 individuals completed a detailed survey. Logistic regression was used to investigate determinants of whether a patient (1) had an opportunity to be weighed at treatment initiation (baseline), and (2) had a weight measurement recorded. Parall

SUBMITTER: Haneuse S 

PROVIDER: S-EPMC4666800 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature