ArticleJournal of the American Medical Informatics Association : JAMIA2026
Institutional approaches to artificial intelligence policy and guidance in health informatics and information management education: emerging trends and inconsistencies.
Article in Journal of the American Medical Informatics Association : JAMIA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo examine the characteristics, scope, and thematic content of institutional and program-level academic artificial intelligence (AI) policies and guidance documents used by CAHIIM-accredited Health Informatics (HI) and Health Information Management (HIM) master's programs in the United States. MATERIALS AND
methodsThis convergent mixed‑methods study examined publicly available AI‑related documents (eg, student handbooks, integrity policies, program manuals) from all 48 CAHIIM‑accredited HI and HIM master's programs listed in November 2025. Forty programs (83%) had at least 1 qualifying document, 8 programs had no qualifying documents. Quantitative analyses summarized policy characteristics and examined associations with delivery modality using Fisher's exact tests. Qualitative analysis applied Latent Dirichlet Allocation topic modeling to identify recurring semantic themes across policy texts.
resultsMost documents provided guidance rather than formal policies; neither policy type nor audience differed by delivery mode. Content emphasized academic integrity, responsible AI use, and expectations for student conduct. References to privacy, intellectual property, and regulatory concepts were present but less common than academic integrity-related themes. Topic modeling identified 4 dominant themes: academic integrity and appropriate AI use; generative AI in teaching; AI and data‑tool use in research; and student engagement with conversational AI systems.
conclusionAI guidance and policy are available across most accredited HI and HIM master's programs; however, they vary in structure and scope. The majority of documents emphasize academic integrity and responsible AI use. Future research could examine how academic program AI policies relate to distinct but related domains such as curriculum development and organizational AI governance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.