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An electronic health record-enabled obesity database

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 deriv...

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Autores principales: Wood, G Craig, Chu, Xin, Manney, Christina, Strodel, William, Petrick, Anthony, Gabrielsen, Jon, Seiler, Jamie, Carey, David, Argyropoulos, George, Benotti, Peter, Still, Christopher D, Gerhard, Glenn S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3508953/
https://www.ncbi.nlm.nih.gov/pubmed/22640398
http://dx.doi.org/10.1186/1472-6947-12-45
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author Wood, G Craig
Chu, Xin
Manney, Christina
Strodel, William
Petrick, Anthony
Gabrielsen, Jon
Seiler, Jamie
Carey, David
Argyropoulos, George
Benotti, Peter
Still, Christopher D
Gerhard, Glenn S
author_facet Wood, G Craig
Chu, Xin
Manney, Christina
Strodel, William
Petrick, Anthony
Gabrielsen, Jon
Seiler, Jamie
Carey, David
Argyropoulos, George
Benotti, Peter
Still, Christopher D
Gerhard, Glenn S
author_sort Wood, G Craig
collection PubMed
description 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.
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spelling pubmed-35089532012-11-29 An electronic health record-enabled obesity database Wood, G Craig Chu, Xin Manney, Christina Strodel, William Petrick, Anthony Gabrielsen, Jon Seiler, Jamie Carey, David Argyropoulos, George Benotti, Peter Still, Christopher D Gerhard, Glenn S BMC Med Inform Decis Mak Research Article 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. BioMed Central 2012-05-28 /pmc/articles/PMC3508953/ /pubmed/22640398 http://dx.doi.org/10.1186/1472-6947-12-45 Text en Copyright ©2012 Wood et al.; licensee BioMed Central Ltd http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Wood, G Craig
Chu, Xin
Manney, Christina
Strodel, William
Petrick, Anthony
Gabrielsen, Jon
Seiler, Jamie
Carey, David
Argyropoulos, George
Benotti, Peter
Still, Christopher D
Gerhard, Glenn S
An electronic health record-enabled obesity database
title An electronic health record-enabled obesity database
title_full An electronic health record-enabled obesity database
title_fullStr An electronic health record-enabled obesity database
title_full_unstemmed An electronic health record-enabled obesity database
title_short An electronic health record-enabled obesity database
title_sort electronic health record-enabled obesity database
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3508953/
https://www.ncbi.nlm.nih.gov/pubmed/22640398
http://dx.doi.org/10.1186/1472-6947-12-45
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