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TRUVACE RECORD VERSION
record: TRV-2026-1538
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-16T06:54:24.379373Z
status: published
lens: p_space
sector: policy
headline: Institutional approaches to artificial intelligence policy and guidance in health informatics and information management education: emerging trends and inconsistencies
dek: Objective To 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 methods This 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 mas…
gain_title: (none)
problem_title: Eight of 48 accredited programs had no qualifying AI document, and the rest varied in structure and scope, mostly offering guidance rather than formal policy.
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: Eight of 48 accredited programs had no qualifying AI document, and the rest varied in structure and scope, mostly offering guidance rather than formal policy.
problem_evidence: 8 programs had no qualifying documents | they vary in structure and scope | Most documents provided guidance rather than formal policies
quick_read: Researchers reviewed publicly available AI-related documents such as student handbooks, integrity policies and program manuals from all 48 CAHIIM-accredited health informatics and health information management master's programs listed in November 2025. They found that 40 programs had at least one qualifying document, while eight had none.

The findings show that students in training for health data roles face inconsistent expectations about AI use, with academic integrity dominating the content. The study did not examine curriculum or organizational AI governance, which the authors flag as areas for later research.
limitation: The study analyzed only publicly available documents, and the authors say links to curriculum development and organizational AI governance remain unexamined.
tag: Evidence-backed problem
key_points: Forty of 48 programs (83%) had at least one qualifying AI-related document; eight had none. | Most documents were guidance rather than formal policies, and neither policy type nor audience differed by delivery mode. | Academic integrity and responsible AI use were the dominant themes, while privacy, intellectual property and regulation appeared less often. | Topic modeling found four themes, including generative AI in teaching and student engagement with conversational AI.
rundown: The study used a convergent mixed-methods design. Quantitative analyses summarized policy characteristics and used Fisher's exact tests to compare delivery modality, while Latent Dirichlet Allocation topic modeling identified recurring semantic themes in the texts.

The four themes were academic integrity and appropriate AI use, generative AI in teaching, AI and data-tool use in research, and student engagement with conversational AI systems.

Privacy, intellectual property and regulatory concepts were present but less common than integrity themes. The authors suggest future work on how program AI policies relate to curriculum development and organizational AI governance.
sources:
- peer_reviewed | Journal of the American Medical Informatics Association | https://doi.org/10.1093/jamia/ocag150 | 2026-10-01
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