Journal:Transforming healthcare analytics with FHIR: A framework for standardizing and analyzing clinical data
| Full article title | Transforming healthcare analytics with FHIR: A framework for standardizing and analyzing clinical data |
|---|---|
| Journal | Healthcare |
| Author(s) | Ayaz, Muhammad; Pasha, Muhammad F.; Alahmadi, Tahani J.; Abdullah, Nik N.B.; Alkahtani, Hend K. |
| Author affiliation(s) | Monash University, Princess Nourah bint Abdulrahman University |
| Primary contact | Email: muhammad dot ayaz at monash dot edu |
| Year published | 2023 |
| Volume and issue | 11(12) |
| Article # | 1729 |
| DOI | 10.3390/healthcare11121729 |
| ISSN | 2227-9032 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | https://www.mdpi.com/2227-9032/11/12/1729 |
| Download | https://www.mdpi.com/2227-9032/11/12/1729/pdf?version=1686738253 (PDF) |
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This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
In this study, we discuss 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 Resources (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 (HIS), namely patient registration and laboratory information systems (LIS). These workflows exploit various FHIR application programming interfaces (API) to facilitate patient-centered and cohort-based interactive analyses. We developed a 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.
Keywords: data analytics, data analysis, FHIR, EMR, EHR
Background
To provide a comprehensive idea to readers about the applications of data analytics in the healthcare industry, this section introduces the data analytics concept employed in the healthcare sector. We also discuss the data analytics concept in the clinical data represented in the latest healthcare data standard, Fast Healthcare Interoperability Resources (FHIR).
References
Notes
This presentation is faithful to the original, with only a few minor changes to presentation, though grammar and word usage was substantially updated for improved readability. In some cases important information was missing from the references, and that information was added.
