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A pragmatic method for electronic medical record-based observational studies: developing an electronic medical records retrieval system for clinical research
OBJECTIVE: The use of electronic medical record (EMR) data is necessary to improve clinical research efficiency. However, it is not easy to identify patients who meet research eligibility criteria and collect the necessary information from EMRs because the data collection process must integrate vari...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Group
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3533000/ https://www.ncbi.nlm.nih.gov/pubmed/23117567 http://dx.doi.org/10.1136/bmjopen-2012-001622 |
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author | Yamamoto, Keiichi Sumi, Eriko Yamazaki, Toru Asai, Keita Yamori, Masashi Teramukai, Satoshi Bessho, Kazuhisa Yokode, Masayuki Fukushima, Masanori |
author_facet | Yamamoto, Keiichi Sumi, Eriko Yamazaki, Toru Asai, Keita Yamori, Masashi Teramukai, Satoshi Bessho, Kazuhisa Yokode, Masayuki Fukushima, Masanori |
author_sort | Yamamoto, Keiichi |
collection | PubMed |
description | OBJECTIVE: The use of electronic medical record (EMR) data is necessary to improve clinical research efficiency. However, it is not easy to identify patients who meet research eligibility criteria and collect the necessary information from EMRs because the data collection process must integrate various techniques, including the development of a data warehouse and translation of eligibility criteria into computable criteria. This research aimed to demonstrate an electronic medical records retrieval system (ERS) and an example of a hospital-based cohort study that identified both patients and exposure with an ERS. We also evaluated the feasibility and usefulness of the method. DESIGN: The system was developed and evaluated. PARTICIPANTS: In total, 800 000 cases of clinical information stored in EMRs at our hospital were used. PRIMARY AND SECONDARY OUTCOME MEASURES: The feasibility and usefulness of the ERS, the method to convert text from eligible criteria to computable criteria, and a confirmation method to increase research data accuracy. RESULTS: To comprehensively and efficiently collect information from patients participating in clinical research, we developed an ERS. To create the ERS database, we designed a multidimensional data model optimised for patient identification. We also devised practical methods to translate narrative eligibility criteria into computable parameters. We applied the system to an actual hospital-based cohort study performed at our hospital and converted the test results into computable criteria. Based on this information, we identified eligible patients and extracted data necessary for confirmation by our investigators and for statistical analyses with our ERS. CONCLUSIONS: We propose a pragmatic methodology to identify patients from EMRs who meet clinical research eligibility criteria. Our ERS allowed for the efficient collection of information on the eligibility of a given patient, reduced the labour required from the investigators and improved the reliability of the results. |
format | Online Article Text |
id | pubmed-3533000 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BMJ Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-35330002013-01-04 A pragmatic method for electronic medical record-based observational studies: developing an electronic medical records retrieval system for clinical research Yamamoto, Keiichi Sumi, Eriko Yamazaki, Toru Asai, Keita Yamori, Masashi Teramukai, Satoshi Bessho, Kazuhisa Yokode, Masayuki Fukushima, Masanori BMJ Open Health Informatics OBJECTIVE: The use of electronic medical record (EMR) data is necessary to improve clinical research efficiency. However, it is not easy to identify patients who meet research eligibility criteria and collect the necessary information from EMRs because the data collection process must integrate various techniques, including the development of a data warehouse and translation of eligibility criteria into computable criteria. This research aimed to demonstrate an electronic medical records retrieval system (ERS) and an example of a hospital-based cohort study that identified both patients and exposure with an ERS. We also evaluated the feasibility and usefulness of the method. DESIGN: The system was developed and evaluated. PARTICIPANTS: In total, 800 000 cases of clinical information stored in EMRs at our hospital were used. PRIMARY AND SECONDARY OUTCOME MEASURES: The feasibility and usefulness of the ERS, the method to convert text from eligible criteria to computable criteria, and a confirmation method to increase research data accuracy. RESULTS: To comprehensively and efficiently collect information from patients participating in clinical research, we developed an ERS. To create the ERS database, we designed a multidimensional data model optimised for patient identification. We also devised practical methods to translate narrative eligibility criteria into computable parameters. We applied the system to an actual hospital-based cohort study performed at our hospital and converted the test results into computable criteria. Based on this information, we identified eligible patients and extracted data necessary for confirmation by our investigators and for statistical analyses with our ERS. CONCLUSIONS: We propose a pragmatic methodology to identify patients from EMRs who meet clinical research eligibility criteria. Our ERS allowed for the efficient collection of information on the eligibility of a given patient, reduced the labour required from the investigators and improved the reliability of the results. BMJ Group 2012-10-31 /pmc/articles/PMC3533000/ /pubmed/23117567 http://dx.doi.org/10.1136/bmjopen-2012-001622 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode. |
spellingShingle | Health Informatics Yamamoto, Keiichi Sumi, Eriko Yamazaki, Toru Asai, Keita Yamori, Masashi Teramukai, Satoshi Bessho, Kazuhisa Yokode, Masayuki Fukushima, Masanori A pragmatic method for electronic medical record-based observational studies: developing an electronic medical records retrieval system for clinical research |
title | A pragmatic method for electronic medical record-based observational studies: developing an electronic medical records retrieval system for clinical research |
title_full | A pragmatic method for electronic medical record-based observational studies: developing an electronic medical records retrieval system for clinical research |
title_fullStr | A pragmatic method for electronic medical record-based observational studies: developing an electronic medical records retrieval system for clinical research |
title_full_unstemmed | A pragmatic method for electronic medical record-based observational studies: developing an electronic medical records retrieval system for clinical research |
title_short | A pragmatic method for electronic medical record-based observational studies: developing an electronic medical records retrieval system for clinical research |
title_sort | pragmatic method for electronic medical record-based observational studies: developing an electronic medical records retrieval system for clinical research |
topic | Health Informatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3533000/ https://www.ncbi.nlm.nih.gov/pubmed/23117567 http://dx.doi.org/10.1136/bmjopen-2012-001622 |
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