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...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-11-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023087947 |
| _version_ | 1797429812458946560 |
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| author | Lin Lawrence Guo Maryann Calligan Emily Vettese Sadie Cook George Gagnidze Oscar Han Jiro Inoue Joshua Lemmon Johnson Li Medhat Roshdi Bohdan Sadovy Steven Wallace Lillian Sung |
| author_facet | Lin Lawrence Guo Maryann Calligan Emily Vettese Sadie Cook George Gagnidze Oscar Han Jiro Inoue Joshua Lemmon Johnson Li Medhat Roshdi Bohdan Sadovy Steven Wallace Lillian Sung |
| author_sort | Lin Lawrence Guo |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T09:18:34Z |
| format | Article |
| id | doaj.art-22dcf145eb9b4594ba52fc879c37547e |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-09T09:18:34Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-22dcf145eb9b4594ba52fc879c37547e2023-12-02T07:03:15ZengElsevierHeliyon2405-84402023-11-01911e21586Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR)Lin Lawrence Guo0Maryann Calligan1Emily Vettese2Sadie Cook3George Gagnidze4Oscar Han5Jiro Inoue6Joshua Lemmon7Johnson Li8Medhat Roshdi9Bohdan Sadovy10Steven Wallace11Lillian Sung12Program in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, CanadaProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, CanadaProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, CanadaProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, CanadaInformation Management Technology, The Hospital for Sick Children, Toronto, CanadaInformation Management Technology, The Hospital for Sick Children, Toronto, CanadaProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, CanadaProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, CanadaInformation Management Technology, The Hospital for Sick Children, Toronto, CanadaInformation Management Technology, The Hospital for Sick Children, Toronto, CanadaInformation Management Technology, The Hospital for Sick Children, Toronto, CanadaInformation Management Technology, The Hospital for Sick Children, Toronto, CanadaProgram in Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Canada; Division of Haematology/Oncology, The Hospital for Sick Children, Toronto, Canada; Corresponding author. The Division of Haematology/Oncology, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, M5G1X8, Canada.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.http://www.sciencedirect.com/science/article/pii/S2405844023087947Electronic health recordsMicrosoft AzureSchemaValidationOMOP-CDM |
| spellingShingle | Lin Lawrence Guo Maryann Calligan Emily Vettese Sadie Cook George Gagnidze Oscar Han Jiro Inoue Joshua Lemmon Johnson Li Medhat Roshdi Bohdan Sadovy Steven Wallace Lillian Sung Development and validation of the SickKids Enterprise-wide Data in Azure Repository (SEDAR) Heliyon Electronic health records Microsoft Azure Schema Validation OMOP-CDM |
| 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 | Electronic health records Microsoft Azure Schema Validation OMOP-CDM |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023087947 |
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