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The Roles of Biomedical Informatics for an Equitable Learning Health System: Lessons from a Year of Scientific Informatics Literature
Journal article   Open access   Peer reviewed

The Roles of Biomedical Informatics for an Equitable Learning Health System: Lessons from a Year of Scientific Informatics Literature

Humayera Islam, Pushkala Jayarman, Nick Reid, Pratishtha Guckhool, Malin Britt-Lalich, Parand Shams, Zihan Xu and James J Cimino
Methods of information in medicine, Forthcoming
13 Aug 2026
DOI: https://doi.org/10.1055/a-2937-0980
PMID: 42594964
url
https://doi.org/10.1055/a-2937-0980View
Published, Version of Record (VoR) Open

Abstract

health equity learning health systems artificial intelligence clinical informatics health care disparities
Biomedical informatics plays a central role in supporting learning health systems (LHSs) which aim to continuously improve care by transforming data into knowledge and knowledge into action. However, healthcare data reflect existing disparities in access, delivery and outcomes, raising concerns whether the LHS cycle can improve care equitably without intentional design. To describe the recurring theme of health equity found in recent biomedical informatics literature, using a convenience sample of articles contributed to the 2025 AMIA Year in Review (YIR). In developing the 2025 AMIA YIR presentation, we found that 240 articles submitted by AMIA experts could be organized into multiple themes to allow summarization and synthesis for efficient presentation of 140 of them. Many themes could themselves be organized around the concept of the learning health system, which further streamlined the presentation. We were struck by the frequency with which the issue of the contribution of biomedical informatics are related to health equity related to learning health systems was addressed. We therefore applied our own expertise to distill relevant articles from the larger set to explore this recurrent issue. Here, we present 56 papers selected from nine of the 19 themes that illustrate how biomedical informatics can support equity at each stage of the LHS. Mature LHS implementations provided large-scale examples of how learning cycles can be designed for equity. Real-world evidence and inclusive data themes showed that equitable learning depends on whether data are complete enough to represent the populations the system intends to serve. Natural language processing and Artificial Intelligence modeling showed how data are transformed into knowledge and translated into clinical action through decision support. Trust and justice in data use, health equity as infrastructure, and equitable access emerged as interdependent conditions that influence whether the learning cycle operates equitably and effectively. Equity emerged as a condition influencing every stage of the LHS cycle. The value of informatics interventions cannot be judged by technical performance alone, but by whether they build learning cycles that are inclusive, accountable, and equitable for the populations they serve.

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