Evidence map›Paper›PMID 42022211›Full record

ArticleAdvances in health information science and practice2026

Integrating Artificial Intelligence Into Health Informatics and Information Education: A Competency-Based Framework Using Miller's Pyramid.

Shannon H Houser, Cathy A Flite, Susan L Foster, Angela Morey

Abstract read
In one paragraph

Article in Advances in health information science and practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shannon H HouserHealth Services Administration, University of Alabama at Birmingham.ORCID https://orcid.org/0000-0003-4846-937X
Cathy A FliteHealth Services Administration and Policy, Temple University.
Susan L FosterHealth Information Management, Florida SouthWestern State College.
Angela MoreyHealth Administration Department, University of North Georgia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integration of artificial intelligence (AI) into health informatics and information management (HIIM) education presents both transformative opportunities and ethical complexities. As health care systems increasingly adopt AI-enabled tools and workflows, educational programs must prepare students to not only understand AI technologies but also apply them responsibly and effectively. In this article, the authors propose a competency-based framework for embedding AI into HIIM curricula, using Miller's Pyramid of Clinical Competence to scaffold progressive learning outcomes. With this developmental model, educators guide students from foundational knowledge to applied reasoning, simulation-based practice, and real-world performance using AI tools. The model can be used to foster problem-solving abilities and support workforce readiness by aligning AI-enhanced assignments with core HIIM domains. Ethical considerations are embedded throughout the learning process to promote the responsible and equitable use of AI. By offering flexible guidance for integrating AI into diverse educational settings, the competency-based framework enables instructors to design competency-aligned learning experiences that foster technical proficiency, ethical awareness, and professional confidence in today's AI-driven health care environment.

Indexed as

Artificial IntelligenceCompetency-Based EducationMedical InformaticsClinical CompetenceCurriculumHumansModels, EducationalAI-enhanced learningartificial intelligencecompetency-based learningeducational frameworkshealth informatics and information educationMiller’s Pyramidresponsible AI in education

Identifiers

PMID42022211
PMCPMC13097619

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.