ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2015
Clinical Predictive Modeling Development and Deployment through FHIR Web Services.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- A machine learning approach to predicting inpatient mortality among pediatric acute gastroenteritis patients in Kenya.Learning health systems · 2025Article
- Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms.BMC medical informatics and decision making · 2025Article
- Predictive modelling of linear growth faltering among pediatric patients with Diarrhea in Rural Western Kenya: an explainable machine learning approach.BMC medical informatics and decision making · 2024Article
- Leveraging Electronic Health Records to Predict the Risk of Acute Kidney Injury after Allogeneic Hematopoietic Cell Transplantation.Life (Basel, Switzerland) · 2024Article
- Machine Learning-Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review.JMIR medical informatics · 2023Article
- Development and validation of common data model-based fracture prediction model using machine learning algorithm.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2023Article
- Transforming Healthcare Analytics with FHIR: A Framework for Standardizing and Analyzing Clinical Data.Healthcare (Basel, Switzerland) · 2023Article
- Development of an Interoperable and Easily Transferable Clinical Decision Support System Deployment Platform: System Design and Development Study.Journal of medical Internet research · 2022Article
- Advancing brain network models to reconcile functional neuroimaging and clinical research.NeuroImage. Clinical · 2022Review
- New Standards for Clinical Decision Support: A Survey of The State of Implementation.Yearbook of medical informatics · 2021Review
- Design and Implementation of an Informatics Infrastructure for Standardized Data Acquisition, Transfer, Storage, and Export in Psychiatric Clinical Routine: Feasibility Study.JMIR mental health · 2021Article
- Toward cross-platform electronic health record-driven phenotyping using Clinical Quality Language.Learning health systems · 2020Article
- EHR-Independent Predictive Decision Support Architecture Based on OMOP.Applied clinical informatics · 2020Article
- An Automated Fast Healthcare Interoperability Resources-Based 12-Lead Electrocardiogram Mobile Alert System for Suspected Acute Coronary Syndrome.Yonsei medical journal · 2020Article
- Experience in Developing an FHIR Medical Data Management Platform to Provide Clinical Decision Support.International journal of environmental research and public health · 2019Article
- Article
- Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community-driven standards.Human mutation · 2018Article
- Patients Decision Aid System Based on FHIR Profiles.Journal of medical systems · 2018Article
- MIRACUM: Medical Informatics in Research and Care in University Medicine.Methods of information in medicine · 2018Article
- Patient-Centered Radiology with FHIR: an Introduction to the Use of FHIR to Offer Radiology a Clinically Integrated Platform.Journal of digital imaging · 2018Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
26958207PMC4765683What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.