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Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure
Observational healthcare databases represent a valuable resource for health economics, outcomes research, quality of care, drug safety, epidemiology and comparative effectiveness research. The methods used to identify a population for study in an observational healthcare database with the desired dr...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3566397/ https://www.ncbi.nlm.nih.gov/pubmed/23396660 http://dx.doi.org/10.1007/s10742-012-0102-1 |
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author | DeFalco, Frank J. Ryan, Patrick B. Soledad Cepeda, M. |
author_facet | DeFalco, Frank J. Ryan, Patrick B. Soledad Cepeda, M. |
author_sort | DeFalco, Frank J. |
collection | PubMed |
description | Observational healthcare databases represent a valuable resource for health economics, outcomes research, quality of care, drug safety, epidemiology and comparative effectiveness research. The methods used to identify a population for study in an observational healthcare database with the desired drug exposures of interest are complex and not consistent nor apparent in the published literature. Our research evaluates three drug classification systems and their impact on prevalence in the analysis of observational healthcare databases using opioids as a case in point. The standard terminologies compiled in the Observational Medical Outcomes Partnership’s Common Data Model vocabulary were used to facilitate the identification of populations with opioid exposures. This study analyzed three distinct observational healthcare databases and identified patients with at least one exposure to an opioid as defined by drug codes derived through the application of three classification systems. Opioid code sets were created for each of the three classification systems and the number of identified codes was summarized. We estimated the prevalence of opioid exposure in three observational healthcare databases using the three defined code sets. In addition we compared the number of drug codes and distinct ingredients that were identified using these classification systems. We found substantial variation in the prevalence of opioid exposure identified using an individual classification system versus a composite method using multiple classification systems. To ensure transparent and reproducible research publications should include a description of the process used to develop code sets and the complete code set used in studies. |
format | Online Article Text |
id | pubmed-3566397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-35663972013-02-08 Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure DeFalco, Frank J. Ryan, Patrick B. Soledad Cepeda, M. Health Serv Outcomes Res Methodol Article Observational healthcare databases represent a valuable resource for health economics, outcomes research, quality of care, drug safety, epidemiology and comparative effectiveness research. The methods used to identify a population for study in an observational healthcare database with the desired drug exposures of interest are complex and not consistent nor apparent in the published literature. Our research evaluates three drug classification systems and their impact on prevalence in the analysis of observational healthcare databases using opioids as a case in point. The standard terminologies compiled in the Observational Medical Outcomes Partnership’s Common Data Model vocabulary were used to facilitate the identification of populations with opioid exposures. This study analyzed three distinct observational healthcare databases and identified patients with at least one exposure to an opioid as defined by drug codes derived through the application of three classification systems. Opioid code sets were created for each of the three classification systems and the number of identified codes was summarized. We estimated the prevalence of opioid exposure in three observational healthcare databases using the three defined code sets. In addition we compared the number of drug codes and distinct ingredients that were identified using these classification systems. We found substantial variation in the prevalence of opioid exposure identified using an individual classification system versus a composite method using multiple classification systems. To ensure transparent and reproducible research publications should include a description of the process used to develop code sets and the complete code set used in studies. Springer US 2012-10-27 2013 /pmc/articles/PMC3566397/ /pubmed/23396660 http://dx.doi.org/10.1007/s10742-012-0102-1 Text en © The Author(s) 2012 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Article DeFalco, Frank J. Ryan, Patrick B. Soledad Cepeda, M. Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure |
title | Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure |
title_full | Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure |
title_fullStr | Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure |
title_full_unstemmed | Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure |
title_short | Applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure |
title_sort | applying standardized drug terminologies to observational healthcare databases: a case study on opioid exposure |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3566397/ https://www.ncbi.nlm.nih.gov/pubmed/23396660 http://dx.doi.org/10.1007/s10742-012-0102-1 |
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