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Pathling: analytics on FHIR
John Grimes1, Piotr Szul2, Alejandro Metke-Jimenez2
1Australian e-Health Research Centre, CSIRO, Level 7, Surgical Treatment and Rehabilitation Service (STARS), Royal Brisbane and Women's Hospital, Herston, 4029, Queensland, Australia. John.Grimes@csiro.au.
Journal of Biomedical Semantics
|September 8, 2022
Summary
New tools are needed for analyzing Fast Healthcare Interoperability Resources (FHIR) data. Pathling offers a FHIR Analytics API to improve health data analytics and terminology integration for researchers.
Area of Science:
- Health Informatics
- Health Data Analytics
Background:
- The health sector's digitization and evolving standards necessitate better tools for analyzing Fast Healthcare Interoperability Resources (FHIR) data.
- Existing tools lack sufficient support for users analyzing FHIR data and clinical terminology.
Purpose of the Study:
- To develop improved tooling for health data analytics.
- To enhance the analysis of Fast Healthcare Interoperability Resources (FHIR) data and associated clinical terminology.
Main Methods:
- Developed a server implementation with a FHIR API featuring new operations for exploratory data analysis (EDA), cohort selection, and data preparation.
- Integrated a FHIR Terminology Service to incorporate knowledge from terminologies like SNOMED CT.
- Created a prototype user interface for EDA with visualizations.
Main Results:
- A FHIR API was implemented to support advanced health data analysis tasks.
- Integration with a FHIR Terminology Service allows for richer query capabilities.
- A prototype EDA interface and visualizations were developed.
Conclusions:
- The Pathling FHIR Analytics API pattern is a valuable abstraction for health data scientists and developers.
- Pathling enhances the utility of FHIR for health data analytics and complex clinical terminology use.
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