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Transforming Healthcare Analytics with FHIR: A Framework for Standardizing and Analyzing Clinical Data.
- Source :
- Healthcare (2227-9032); Jun2023, Vol. 11 Issue 12, p1729, 28p
- Publication Year :
- 2023
-
Abstract
- In this study, we discussed our contribution to building a data analytic framework that supports clinical statistics and analysis by leveraging a scalable standards-based data model named Fast Healthcare Interoperability Resource (FHIR). We developed an intelligent algorithm that is used to facilitate the clinical data analytics process on FHIR-based data. We designed several workflows for patient clinical data used in two hospital information systems, namely patient registration and laboratory information systems. These workflows exploit various FHIR Application programming interface (APIs) to facilitate patient-centered and cohort-based interactive analyses. We developed an FHIR database implementation that utilizes FHIR APIs and a range of operations to facilitate descriptive data analytics (DDA) and patient cohort selection. A prototype user interface for DDA was developed with support for visualizing healthcare data analysis results in various forms. Healthcare professionals and researchers would use the developed framework to perform analytics on clinical data used in healthcare settings. Our experimental results demonstrate the proposed framework's ability to generate various analytics from clinical data represented in the FHIR resources. [ABSTRACT FROM AUTHOR]
- Subjects :
- EVALUATION of medical care
HEALTH care industry
ELECTRONIC data interchange
MEDICAL information storage & retrieval systems
PATIENT-centered care
CONCEPTUAL structures
WORKFLOW
MEDICAL laboratories
RESEARCH funding
ELECTRONIC health records
DATA analytics
HOSPITAL information systems
ALGORITHMS
LONGITUDINAL method
Subjects
Details
- Language :
- English
- ISSN :
- 22279032
- Volume :
- 11
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- Healthcare (2227-9032)
- Publication Type :
- Academic Journal
- Accession number :
- 164651587
- Full Text :
- https://doi.org/10.3390/healthcare11121729