| Literature DB >> 26958207 |
Mohammed Khalilia1, Myung Choi1, Amelia Henderson1, Sneha Iyengar1, Mark Braunstein1, Jimeng Sun1.
Abstract
Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction.Entities:
Mesh:
Year: 2015 PMID: 26958207 PMCID: PMC4765683
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076