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An electronic health record-enabled obesity database

Identifieur interne : 000101 ( Pmc/Corpus ); précédent : 000100; suivant : 000102

An electronic health record-enabled obesity database

Auteurs : G Craig Wood ; Xin Chu ; Christina Manney ; William Strodel ; Anthony Petrick ; Jon Gabrielsen ; Jamie Seiler ; David Carey ; George Argyropoulos ; Peter Benotti ; Christopher D. Still ; Glenn S. Gerhard

Source :

RBID : PMC:3508953

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.


Url:
DOI: 10.1186/1472-6947-12-45
PubMed: 22640398
PubMed Central: 3508953

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Data generation: Sat Nov 11 16:53:45 2017. Site generation: Mon Mar 11 23:15:16 2024