An electronic health record-enabled obesity database
<p>Abstract</p> <p>Background</p> <p>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...
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BMC
2012-05-01
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Series: | BMC Medical Informatics and Decision Making |
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Online Access: | http://www.biomedcentral.com/1472-6947/12/45 |
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author | Wood G 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 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 |
collection | DOAJ |
description | <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>A variety of EHR-derived data related to obesity can be efficiently obtained and used to study important outcomes following RYGB.</p> |
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id | doaj.art-0192ca78311a4f79803390f4cc1baaf6 |
institution | Directory Open Access Journal |
issn | 1472-6947 |
language | English |
last_indexed | 2024-04-12T14:29:19Z |
publishDate | 2012-05-01 |
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series | BMC Medical Informatics and Decision Making |
spelling | doaj.art-0192ca78311a4f79803390f4cc1baaf62022-12-22T03:29:21ZengBMCBMC Medical Informatics and Decision Making1472-69472012-05-011214510.1186/1472-6947-12-45An electronic health record-enabled obesity databaseWood GChu XinManney ChristinaStrodel WilliamPetrick AnthonyGabrielsen JonSeiler JamieCarey DavidArgyropoulos GeorgeBenotti PeterStill Christopher DGerhard Glenn S<p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>A variety of EHR-derived data related to obesity can be efficiently obtained and used to study important outcomes following RYGB.</p>http://www.biomedcentral.com/1472-6947/12/45EHRDatabaseWeight lossModelingObesity |
spellingShingle | Wood G 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 BMC Medical Informatics and Decision Making EHR Database Weight loss Modeling Obesity |
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 | EHR Database Weight loss Modeling Obesity |
url | http://www.biomedcentral.com/1472-6947/12/45 |
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