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Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR)
OBJECTIVES: To describe the processes developed by The Hospital for Sick Children (SickKids) to enable utilization of electronic health record (EHR) data by creating sequentially transformed schemas for use across multiple user types. METHODS: We used Microsoft Azure as the cloud service provider an...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10661187/ https://www.ncbi.nlm.nih.gov/pubmed/38027579 http://dx.doi.org/10.1016/j.heliyon.2023.e21586 |
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author | Guo, Lin Lawrence Calligan, Maryann Vettese, Emily Cook, Sadie Gagnidze, George Han, Oscar Inoue, Jiro Lemmon, Joshua Li, Johnson Roshdi, Medhat Sadovy, Bohdan Wallace, Steven Sung, Lillian |
author_facet | Guo, Lin Lawrence Calligan, Maryann Vettese, Emily Cook, Sadie Gagnidze, George Han, Oscar Inoue, Jiro Lemmon, Joshua Li, Johnson Roshdi, Medhat Sadovy, Bohdan Wallace, Steven Sung, Lillian |
author_sort | Guo, Lin Lawrence |
collection | PubMed |
description | OBJECTIVES: To describe the processes developed by The Hospital for Sick Children (SickKids) to enable utilization of electronic health record (EHR) data by creating sequentially transformed schemas for use across multiple user types. METHODS: We used Microsoft Azure as the cloud service provider and named this effort the SickKids Enterprise-wide Data in Azure Repository (SEDAR). Epic Clarity data from on-premises was copied to a virtual network in Microsoft Azure. Three sequential schemas were developed. The Filtered Schema added a filter to retain only SickKids and valid patients. The Curated Schema created a data structure that was easier to navigate and query. Each table contained a logical unit such as patients, hospital encounters or laboratory tests. Data validation of randomly sampled observations in the Curated Schema was performed. The SK-OMOP Schema was designed to facilitate research and machine learning. Two individuals mapped medical elements to standard Observational Medical Outcomes Partnership (OMOP) concepts. RESULTS: A copy of Clarity data was transferred to Microsoft Azure and updated each night using log shipping. The Filtered Schema and Curated Schema were implemented as stored procedures and executed each night with incremental updates or full loads. Data validation required up to 16 iterations for each Curated Schema table. OMOP concept mapping achieved at least 80 % coverage for each SK-OMOP table. CONCLUSIONS: We described our experience in creating three sequential schemas to address different EHR data access requirements. Future work should consider replicating this approach at other institutions to determine whether approaches are generalizable. |
format | Online Article Text |
id | pubmed-10661187 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-106611872023-11-02 Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR) Guo, Lin Lawrence Calligan, Maryann Vettese, Emily Cook, Sadie Gagnidze, George Han, Oscar Inoue, Jiro Lemmon, Joshua Li, Johnson Roshdi, Medhat Sadovy, Bohdan Wallace, Steven Sung, Lillian Heliyon Research Article OBJECTIVES: To describe the processes developed by The Hospital for Sick Children (SickKids) to enable utilization of electronic health record (EHR) data by creating sequentially transformed schemas for use across multiple user types. METHODS: We used Microsoft Azure as the cloud service provider and named this effort the SickKids Enterprise-wide Data in Azure Repository (SEDAR). Epic Clarity data from on-premises was copied to a virtual network in Microsoft Azure. Three sequential schemas were developed. The Filtered Schema added a filter to retain only SickKids and valid patients. The Curated Schema created a data structure that was easier to navigate and query. Each table contained a logical unit such as patients, hospital encounters or laboratory tests. Data validation of randomly sampled observations in the Curated Schema was performed. The SK-OMOP Schema was designed to facilitate research and machine learning. Two individuals mapped medical elements to standard Observational Medical Outcomes Partnership (OMOP) concepts. RESULTS: A copy of Clarity data was transferred to Microsoft Azure and updated each night using log shipping. The Filtered Schema and Curated Schema were implemented as stored procedures and executed each night with incremental updates or full loads. Data validation required up to 16 iterations for each Curated Schema table. OMOP concept mapping achieved at least 80 % coverage for each SK-OMOP table. CONCLUSIONS: We described our experience in creating three sequential schemas to address different EHR data access requirements. Future work should consider replicating this approach at other institutions to determine whether approaches are generalizable. Elsevier 2023-11-02 /pmc/articles/PMC10661187/ /pubmed/38027579 http://dx.doi.org/10.1016/j.heliyon.2023.e21586 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Guo, Lin Lawrence Calligan, Maryann Vettese, Emily Cook, Sadie Gagnidze, George Han, Oscar Inoue, Jiro Lemmon, Joshua Li, Johnson Roshdi, Medhat Sadovy, Bohdan Wallace, Steven Sung, Lillian Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR) |
title | Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR) |
title_full | Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR) |
title_fullStr | Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR) |
title_full_unstemmed | Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR) |
title_short | Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR) |
title_sort | development and validation of the sickkids enterprise-wide data in azure repository (sedar) |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10661187/ https://www.ncbi.nlm.nih.gov/pubmed/38027579 http://dx.doi.org/10.1016/j.heliyon.2023.e21586 |
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