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Artificial Intelligence in Health

REVIEW ARTICLE
Optimizing electronic health records to support

artificial intelligence

Evelyn J. S. Hovenga * and Koray Atalag 3
1,2
1 Department of Digital Health, Faculty of Health Sciences, Australian Catholic University, Fitzroy,
Victoria, Australia
2 eHealth Education Pty Ltd, Abbotsford, Victoria, Australia
3 GALATA-Digital LLC-FZ, Dubai, United Arab Emirates

Abstract

Electronic health records (EHRs) provide the most important data sources for artificial
intelligence (AI). Gaining access to quality data suitable for advanced analytics
continues to be challenging. This rapid review documents the current state of
available data; identifies foundational AI data/information needs; and explores the
benefits of adopting new and emerging technologies to design and implement next-
generation EHRs. Opportunities to optimize EHRs for AI purposes are identified. This
review was informed by expert knowledge and shared experiences supported by the
literature, including technical standards. Main findings include poor ecosystem-wide
infrastructures due to the lack of adopting the right set of standards, and current data
and knowledge governance no longer fit for purpose. While many jurisdictions are
continuing the use of legacy systems, some forward-looking national health systems
and health-care facilities are adopting transformational strategies by adopting
a strong data and digital focus to transition to new-generation systems. New
*Corresponding author: foundational-level national infrastructures with strong leadership and governance
Evelyn J.S. Hovenga are essential to enhance the governance and quality of available data, from collection
(e.hovenga@ehe.edu.au) at source throughout the entire data supply chain. Secure and ubiquitous access
Citation: Hovenga EJS, Atalag K. to high-quality EHR data at scale will foster the evolution of more intelligent and
Optimizing electronic health records trustworthy AI. Key characteristics of next-generation EHRs supported by currently
to support artificial intelligence.
Artif Intell Health. 2024;1(3):10-25. available technologies and standards that are able to meet digital era demands are
doi: 10.36922/aih.3056 provided in this paper. We conclude that the use of generative AI in clinical settings
Received: February 29, 2024 can only be reliably achieved when EHRs are optimized throughout the entire global
digital health ecosystem.
Accepted: June 5, 2024
Published Online: July 24, 2024
Keywords: Ontology; Standards; Terminology; System architecture; Models; Data;
Copyright: © 2024 Author(s). Electronic health records
This is an Open-Access article
distributed under the terms of the
Creative Commons Attribution
License, permitting distribution,
and reproduction in any medium, 1. Introduction
provided the original work is
properly cited. Artificial intelligence (AI), which has progressed concurrently with the introduction
Publisher’s Note: AccScience and adoption of computers, has attained immense developments in recent years. The
Publishing remains neutral with collective utilization of data science, AI, information, and communication technologies
regard to jurisdictional claims in can potentially enhance or transform the health-care industry. Their successful use
published maps and institutional
affiliations. augments the potential for people to gain a greater insight into any health-related

Volume 1 Issue 3 (2024) 10 doi: 10.36922/aih.3056