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Assessing an Electronic Health Record research platform for identification of clinical trial participants
Electronic health records (EHR) are a potential resource for identification of clinical trial participants. We evaluated how accurately a commercially available EHR Research Platform, InSite, is able to identify potential trial participants from the EHR system of a large tertiary care hospital. Pati...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773855/ https://www.ncbi.nlm.nih.gov/pubmed/33409423 http://dx.doi.org/10.1016/j.conctc.2020.100692 |
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author | Laaksonen, Niina Varjonen, Juha-Matti Blomster, Minna Palomäki, Antti Vasankari, Tuija Airaksinen, Juhani Huupponen, Risto Scheinin, Mika Juuso Blomster |
author_facet | Laaksonen, Niina Varjonen, Juha-Matti Blomster, Minna Palomäki, Antti Vasankari, Tuija Airaksinen, Juhani Huupponen, Risto Scheinin, Mika Juuso Blomster |
author_sort | Laaksonen, Niina |
collection | PubMed |
description | Electronic health records (EHR) are a potential resource for identification of clinical trial participants. We evaluated how accurately a commercially available EHR Research Platform, InSite, is able to identify potential trial participants from the EHR system of a large tertiary care hospital. Patient counts were compared with results obtained in a conventional manual search performed for a reference study that investigated the associations of atrial fibrillation (AF) and cerebrovascular incidents. The Clinical Data Warehouse (CDW) of Turku University Hospital was used to verify the capabilities of the EHR Research Platform. The EHR query resulted in a larger patient count than the manual query (EHR Research Platform 5859 patients, manual selection 2166 patients). This was due to the different search logic and some exclusion criteria that were not addressable in structured digital format. The EHR Research Platform (5859 patients) and the CDW search (5840 patients) employed the same search logic. The temporal relationship between the two diagnoses could be identified when they were available in structured format and the time difference was longer than a single hospital visit. Searching for patients with the EHR Research Platform can help to identify potential trial participants from a hospital's EHR system by limiting the number of records to be manually reviewed. EHR query tools can best be utilized in trials where the selection criteria are expressed in structured digital format. |
format | Online Article Text |
id | pubmed-7773855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-77738552021-01-05 Assessing an Electronic Health Record research platform for identification of clinical trial participants Laaksonen, Niina Varjonen, Juha-Matti Blomster, Minna Palomäki, Antti Vasankari, Tuija Airaksinen, Juhani Huupponen, Risto Scheinin, Mika Juuso Blomster Contemp Clin Trials Commun Article Electronic health records (EHR) are a potential resource for identification of clinical trial participants. We evaluated how accurately a commercially available EHR Research Platform, InSite, is able to identify potential trial participants from the EHR system of a large tertiary care hospital. Patient counts were compared with results obtained in a conventional manual search performed for a reference study that investigated the associations of atrial fibrillation (AF) and cerebrovascular incidents. The Clinical Data Warehouse (CDW) of Turku University Hospital was used to verify the capabilities of the EHR Research Platform. The EHR query resulted in a larger patient count than the manual query (EHR Research Platform 5859 patients, manual selection 2166 patients). This was due to the different search logic and some exclusion criteria that were not addressable in structured digital format. The EHR Research Platform (5859 patients) and the CDW search (5840 patients) employed the same search logic. The temporal relationship between the two diagnoses could be identified when they were available in structured format and the time difference was longer than a single hospital visit. Searching for patients with the EHR Research Platform can help to identify potential trial participants from a hospital's EHR system by limiting the number of records to be manually reviewed. EHR query tools can best be utilized in trials where the selection criteria are expressed in structured digital format. Elsevier 2020-12-18 /pmc/articles/PMC7773855/ /pubmed/33409423 http://dx.doi.org/10.1016/j.conctc.2020.100692 Text en © 2020 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Laaksonen, Niina Varjonen, Juha-Matti Blomster, Minna Palomäki, Antti Vasankari, Tuija Airaksinen, Juhani Huupponen, Risto Scheinin, Mika Juuso Blomster Assessing an Electronic Health Record research platform for identification of clinical trial participants |
title | Assessing an Electronic Health Record research platform for identification of clinical trial participants |
title_full | Assessing an Electronic Health Record research platform for identification of clinical trial participants |
title_fullStr | Assessing an Electronic Health Record research platform for identification of clinical trial participants |
title_full_unstemmed | Assessing an Electronic Health Record research platform for identification of clinical trial participants |
title_short | Assessing an Electronic Health Record research platform for identification of clinical trial participants |
title_sort | assessing an electronic health record research platform for identification of clinical trial participants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7773855/ https://www.ncbi.nlm.nih.gov/pubmed/33409423 http://dx.doi.org/10.1016/j.conctc.2020.100692 |
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