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Essaid S, Andre J, Brooks IM, Hohman KH, Hull M, Jackson SL, Kahn MG, Kraus EM, Mandadi N, Martinez AK, Mui JY, Zambarano B, Soares A. MENDS-on-FHIR: leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance. JAMIA Open 2024; 7:ooae045. [PMID: 38818114 PMCID: PMC11137321 DOI: 10.1093/jamiaopen/ooae045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 02/20/2024] [Accepted: 05/10/2024] [Indexed: 06/01/2024] Open
Abstract
Objectives The Multi-State EHR-Based Network for Disease Surveillance (MENDS) is a population-based chronic disease surveillance distributed data network that uses institution-specific extraction-transformation-load (ETL) routines. MENDS-on-FHIR examined using Health Language Seven's Fast Healthcare Interoperability Resources (HL7® FHIR®) and US Core Implementation Guide (US Core IG) compliant resources derived from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to create a standards-based ETL pipeline. Materials and Methods The input data source was a research data warehouse containing clinical and administrative data in OMOP CDM Version 5.3 format. OMOP-to-FHIR transformations, using a unique JavaScript Object Notation (JSON)-to-JSON transformation language called Whistle, created FHIR R4 V4.0.1/US Core IG V4.0.0 conformant resources that were stored in a local FHIR server. A REST-based Bulk FHIR $export request extracted FHIR resources to populate a local MENDS database. Results Eleven OMOP tables were used to create 10 FHIR/US Core compliant resource types. A total of 1.13 trillion resources were extracted and inserted into the MENDS repository. A very low rate of non-compliant resources was observed. Discussion OMOP-to-FHIR transformation results passed validation with less than a 1% non-compliance rate. These standards-compliant FHIR resources provided standardized data elements required by the MENDS surveillance use case. The Bulk FHIR application programming interface (API) enabled population-level data exchange using interoperable FHIR resources. The OMOP-to-FHIR transformation pipeline creates a FHIR interface for accessing OMOP data. Conclusion MENDS-on-FHIR successfully replaced custom ETL with standards-based interoperable FHIR resources using Bulk FHIR. The OMOP-to-FHIR transformations provide an alternative mechanism for sharing OMOP data.
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Affiliation(s)
- Shahim Essaid
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
| | - Jeff Andre
- Commonwealth Informatics Inc, Waltham, MA 02451, United States
| | - Ian M Brooks
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
| | - Katherine H Hohman
- National Association of Chronic Disease Directors (NACDD), Decatur, GA 30030, United States
| | - Madelyne Hull
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
| | - Sandra L Jackson
- National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), Atlanta, GA 30333, United States
| | - Michael G Kahn
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
| | - Emily M Kraus
- Kraushold Consulting, Denver, CO 80120, United States
- Public Health Informatics Institute, Decatur, GA 30030, United States
| | - Neha Mandadi
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
| | - Amanda K Martinez
- National Association of Chronic Disease Directors (NACDD), Decatur, GA 30030, United States
| | - Joyce Y Mui
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
| | - Bob Zambarano
- Commonwealth Informatics Inc, Waltham, MA 02451, United States
| | - Andrey Soares
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO 80045, United States
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Essaid S, Andre J, Brooks IM, Hohman KH, Hull M, Jackson SL, Kahn MG, Kraus EM, Mandadi N, Martinez AK, Mui JY, Zambarano B, Soares A. MENDS-on-FHIR: Leveraging the OMOP common data model and FHIR standards for national chronic disease surveillance. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.09.23293900. [PMID: 38045364 PMCID: PMC10690355 DOI: 10.1101/2023.08.09.23293900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Objective The Multi-State EHR-Based Network for Disease Surveillance (MENDS) is a population-based chronic disease surveillance distributed data network that uses institution-specific extraction-transformation-load (ETL) routines. MENDS-on-FHIR examined using Health Language Seven's Fast Healthcare Interoperability Resources (HL7® FHIR®) and US Core Implementation Guide (US Core IG) compliant resources derived from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to create a standards-based ETL pipeline. Materials and Methods The input data source was a research data warehouse containing clinical and administrative data in OMOP CDM Version 5.3 format. OMOP-to-FHIR transformations, using a unique JavaScript Object Notation (JSON)-to-JSON transformation language called Whistle, created FHIR R4 V4.0.1/US Core IG V4.0.0 conformant resources that were stored in a local FHIR server. A REST-based Bulk FHIR $export request extracted FHIR resources to populate a local MENDS database. Results Eleven OMOP tables were used to create 10 FHIR/US Core compliant resource types. A total of 1.13 trillion resources were extracted and inserted into the MENDS repository. A very low rate of non-compliant resources was observed. Discussion OMOP-to-FHIR transformation results passed validation with less than a 1% non-compliance rate. These standards-compliant FHIR resources provided standardized data elements required by the MENDS surveillance use case. The Bulk FHIR application programming interface (API) enabled population-level data exchange using interoperable FHIR resources. The OMOP-to-FHIR transformation pipeline creates a FHIR interface for accessing OMOP data. Conclusion MENDS-on-FHIR successfully replaced custom ETL with standards-based interoperable FHIR resources using Bulk FHIR. The OMOP-to-FHIR transformations provide an alternative mechanism for sharing OMOP data.
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Affiliation(s)
- Shahim Essaid
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver CO
| | - Jeff Andre
- Commonwealth Informatics Inc, Waltham MA
| | - Ian M Brooks
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver CO
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver CO
| | | | - Madelyne Hull
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver CO
| | - Sandra L Jackson
- National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention (CDC), Atlanta GA
| | - Michael G Kahn
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver CO
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver CO
| | - Emily M Kraus
- Kraushold Consulting, Denver CO
- Public Health Informatics Institute, Decatur, GA
| | - Neha Mandadi
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver CO
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver CO
| | - Amanda K Martinez
- National Association of Chronic Disease Directors (NACDD), Decatur GA
| | - Joyce Y Mui
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Denver CO
- Health Data Compass, University of Colorado Anschutz Medical Campus, Denver CO
| | | | - Andrey Soares
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver CO
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