TY - JOUR
T1 - Cumulus
T2 - a federated electronic health record-based learning system powered by Fast Healthcare Interoperability Resources and artificial intelligence
AU - McMurry, Andrew J.
AU - Gottlieb, Daniel I.
AU - Miller, Timothy A.
AU - Jones, James R.
AU - Atreja, Ashish
AU - Crago, Jennifer
AU - Desai, Pankaja M.
AU - Dixon, Brian E.
AU - Garber, Matthew
AU - Ignatov, Vladimir
AU - Kirchner, Lyndsey A.
AU - Payne, Philip R.O.
AU - Saldanha, Anil J.
AU - Shankar, Prabhu R.V.
AU - Solad, Yauheni V.
AU - Sprouse, Elizabeth A.
AU - Terry, Michael
AU - Wilcox, Adam B.
AU - Mandl, Kenneth D.
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/8/1
Y1 - 2024/8/1
N2 - Objective: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app "listener"that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API). Methods: We advance a model for scalable, federated, data sharing and learning. Cumulus software is designed to address key technology and policy desiderata including local utility, control, and administrative simplicity as well as privacy preservation during robust data sharing, and artificial intelligence (AI) for processing unstructured text. Results: Cumulus relies on containerized, cloud-hosted software, installed within a healthcare organization's security envelope. Cumulus accesses EHR data via the Bulk FHIR interface and streamlines automated processing and sharing. The modular design enables use of the latest AI and natural language processing tools and supports provider autonomy and administrative simplicity. In an initial test, Cumulus was deployed across 5 healthcare systems each partnered with public health. Cumulus output is patient counts which were aggregated into a table stratifying variables of interest to enable population health studies. All code is available open source. A policy stipulating that only aggregate data leave the institution greatly facilitated data sharing agreements. Discussion and Conclusion: Cumulus addresses barriers to data sharing based on (1) federally required support for standard APIs, (2) increasing use of cloud computing, and (3) advances in AI. There is potential for scalability to support learning across myriad network configurations and use cases.
AB - Objective: To address challenges in large-scale electronic health record (EHR) data exchange, we sought to develop, deploy, and test an open source, cloud-hosted app "listener"that accesses standardized data across the SMART/HL7 Bulk FHIR Access application programming interface (API). Methods: We advance a model for scalable, federated, data sharing and learning. Cumulus software is designed to address key technology and policy desiderata including local utility, control, and administrative simplicity as well as privacy preservation during robust data sharing, and artificial intelligence (AI) for processing unstructured text. Results: Cumulus relies on containerized, cloud-hosted software, installed within a healthcare organization's security envelope. Cumulus accesses EHR data via the Bulk FHIR interface and streamlines automated processing and sharing. The modular design enables use of the latest AI and natural language processing tools and supports provider autonomy and administrative simplicity. In an initial test, Cumulus was deployed across 5 healthcare systems each partnered with public health. Cumulus output is patient counts which were aggregated into a table stratifying variables of interest to enable population health studies. All code is available open source. A policy stipulating that only aggregate data leave the institution greatly facilitated data sharing agreements. Discussion and Conclusion: Cumulus addresses barriers to data sharing based on (1) federally required support for standard APIs, (2) increasing use of cloud computing, and (3) advances in AI. There is potential for scalability to support learning across myriad network configurations and use cases.
KW - electronic health record
KW - federated networks
KW - interoperability
KW - public health
UR - http://www.scopus.com/inward/record.url?scp=85199163539&partnerID=8YFLogxK
U2 - 10.1093/jamia/ocae130
DO - 10.1093/jamia/ocae130
M3 - Article
C2 - 38860521
AN - SCOPUS:85199163539
SN - 1067-5027
VL - 31
SP - 1638
EP - 1647
JO - Journal of the American Medical Informatics Association
JF - Journal of the American Medical Informatics Association
IS - 8
ER -