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Bias in recording of body mass index data in the electronic health record.

Authors :
Rea S
Bailey KR
Pathak J
Haug PJ
Source :
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science [AMIA Jt Summits Transl Sci Proc] 2013 Mar 18; Vol. 2013, pp. 214-8. Date of Electronic Publication: 2013 Mar 18 (Print Publication: 2013).
Publication Year :
2013

Abstract

The relationship between patient disease status and the presence or absence of body mass index (BMI) data in the electronic health record (EHR) has not been characterized. We conducted a descriptive study of the completeness of BMI data for three patient cohorts. Cross-sectional descriptions of BMI presence rates per patient were compared between a cohort having at least one ICD-9-CM code for diabetes mellitus (DM) versus a cohort with no diagnosis constraints. Conversely, frequencies of encounter diagnoses were compared among subgroups having BMI recorded or not in both cohorts described and a third cohort having DM codes from a separate organization's EHR. The data demonstrate a correlation with presence of BMI and higher disease status. This effect may bias the cohort average BMIs, which appear higher than expected. When EHR BMI data are repurposed for research, biases in the selective recording of BMI may affect the results.

Details

Language :
English
ISSN :
2153-4063
Volume :
2013
Database :
MEDLINE
Journal :
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Publication Type :
Academic Journal
Accession number :
24303267