Learning About Missing Data Mechanisms in Electronic Health Records-based Research: A Survey-based Approach.
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. Parallel analyses were conducted to investigate missingness during follow-up. Throughout, inverse-probability weighting was used to adjust for the design and survey nonresponse. Analyses were also conducted to investigate potential recall bias.


RESULTS
Missingness at baseline and during follow-up was associated with numerous factors not routinely collected in the EHR including whether or not the patient had ever chosen not to be weighed, external weight control activities, and self-reported baseline weight. Patient attitudes about their weight and perceptions regarding the potential impact of their depression treatment on weight were not related to missingness.


CONCLUSIONS
Adopting a comprehensive strategy to investigate missingness early in the research process gives researchers information necessary to evaluate key assumptions. While the survey presented focuses on outcome data, the overarching strategy can be applied to any and all data elements subject to missingness.
From the aHarvard T.H. Chan School of Public Health, Boston, MA; bRAND Corporation, Santa Monica, CA; and cGroup Health Research Institute, Seattle, WA.
Sebastien
S
Haneuse
Andy
A
Bogart
Ina
I
Jazic
Emily O
EO
Westbrook
Denise
D
Boudreau
Mary Kay
MK
Theis
Greg E
GE
Simon
David
D
Arterburn
D000293:Adolescent; D000328:Adult; D000368:Aged; D000928:Antidepressive Agents / Q000009:adverse effects* / Q000627:therapeutic use; D015982:Bias; D003863:Depression / Q000188:drug therapy*; D057286:Electronic Health Records; D015340:Epidemiologic Research Design; D005260:Female; D019538:Health Care Surveys; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D015430:Weight Gain / Q000187:drug effects*; D015431:Weight Loss / Q000187:drug effects*; D055815:Young Adult
D000928:Antidepressive Agents