Integrating population- and patient-level data for secondary use of electronic health records to study overweight and obesity

Caryn Roth, Chaitanya P. Shivade, Randi E. Foraker, Peter J. Embi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

We combined patient-level clinical data derived from the Electronic Health Record (EHR) with area-level environmental and socioeconomic data to study factors independently associated with overweight and obesity. Our multinomial logistic regression model showed that area-level factors such as farmers' markets, grocery stores and percent college-educated at the zip code level were significantly associated with the outcomes. However, mismatch in the granularity of community and clinical data limited us in creating a discriminatory model. While these results are promising, they reveal challenges that must be overcome in order to maximize secondary use of EHR data to further explore population health status.

Original languageEnglish
Title of host publicationMEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics
PublisherIOS Press
Number of pages1
Edition1-2
ISBN (Print)9781614992882
DOIs
StatePublished - Jan 1 2013
Externally publishedYes
Event14th World Congress on Medical and Health Informatics, MEDINFO 2013 - Copenhagen, Denmark
Duration: Aug 20 2013Aug 23 2013

Publication series

NameStudies in Health Technology and Informatics
Number1-2
Volume192
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

Conference14th World Congress on Medical and Health Informatics, MEDINFO 2013
CountryDenmark
CityCopenhagen
Period08/20/1308/23/13

Keywords

  • Electronic Health Record
  • Obesity
  • Public Health
  • Secondary Use

Fingerprint Dive into the research topics of 'Integrating population- and patient-level data for secondary use of electronic health records to study overweight and obesity'. Together they form a unique fingerprint.

Cite this