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Open Access Research article

An electronic health record-enabled obesity database

G Craig Wood12, Xin Chu13, Christina Manney1, William Strodel4, Anthony Petrick4, Jon Gabrielsen4, Jamie Seiler1, David Carey3, George Argyropoulos13, Peter Benotti5, Christopher D Still1 and Glenn S Gerhard13*

Author Affiliations

1 Geisinger Obesity Research Institute, Geisinger Clinic, Danville, PA, 17822, USA

2 Center for Health Research, Danville, PA, 17822, USA

3 Weis Center for Research, Geisinger Clinic, Danville, PA, 17822, USA

4 Department of Surgery, Geisinger Medical Center, Danville, PA, 17822, USA

5 Department of Surgery, St. Francis Medical Center, Trenton, NJ, USA

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BMC Medical Informatics and Decision Making 2012, 12:45  doi:10.1186/1472-6947-12-45

Published: 28 May 2012

Abstract

Background

The effectiveness of weight loss therapies is commonly measured using body mass index and other obesity-related variables. Although these data are often stored in electronic health records (EHRs) and potentially very accessible, few studies on obesity and weight loss have used data derived from EHRs. We developed processes for obtaining data from the EHR in order to construct a database on patients undergoing Roux-en-Y gastric bypass (RYGB) surgery.

Methods

Clinical data obtained as part of standard of care in a bariatric surgery program at an integrated health delivery system were extracted from the EHR and deposited into a data warehouse. Data files were extracted, cleaned, and stored in research datasets. To illustrate the utility of the data, Kaplan-Meier analysis was used to estimate length of post-operative follow-up.

Results

Demographic, laboratory, medication, co-morbidity, and survey data were obtained from 2028 patients who had undergone RYGB at the same institution since 2004. Pre-and post-operative diagnostic and prescribing information were available on all patients, while survey laboratory data were available on a majority of patients. The number of patients with post-operative laboratory test results varied by test. Based on Kaplan-Meier estimates, over 74% of patients had post-operative weight data available at 4 years.

Conclusion

A variety of EHR-derived data related to obesity can be efficiently obtained and used to study important outcomes following RYGB.

Keywords:
EHR; Database; Weight loss; Modeling; Obesity