Evidence map›Paper›PMID 39657218›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2025

Regulation of artificial intelligence in healthcare: Clinical Laboratory Improvement Amendments (CLIA) as a model.

Brian R Jackson, Mark P Sendak, Anthony Solomonides, Suresh Balu, Dean F Sittig

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. Hot topics in artificial intelligence.Journal of the American Medical Informatics Association : JAMIA · 2025
    Article
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

5 authors.

Brian R JacksonDepartment of Pathology, University of Utah, Salt Lake City, UT 84112, United States.ORCID 0000-0001-7902-3990
Mark P SendakDuke Institute for Health Innovation, Duke University, Durham, NC 27701, United States.ORCID 0000-0001-5828-4497
Anthony SolomonidesResearch Institute, Endeavor Health, Evanston, IL 60210, United States.ORCID 0000-0003-2117-2461
Suresh BaluDuke Institute for Health Innovation, Duke University, Durham, NC 27701, United States.
Dean F SittigDepartment of Clinical and Health Informatics, University of Texas Health Science Center at Houston, Houston, TX 77030, United States.

Funding

Informatics Review LLC
6 · The paper itself

Abstract

objectivesTo assess the potential to adapt an existing technology regulatory model, namely the Clinical Laboratory Improvement Amendments (CLIA), for clinical artificial intelligence (AI). MATERIALS AND

methodsWe identify overlap in the quality management requirements for laboratory testing and clinical AI.

resultsWe propose modifications to the CLIA model that could make it suitable for oversight of clinical AI. DISCUSSION: In national discussions of clinical AI, there has been surprisingly little consideration of this longstanding model for local technology oversight. While CLIA was specifically designed for laboratory testing, most of its principles are applicable to other technologies in patient care.

conclusionA CLIA-like approach to regulating clinical AI would be complementary to the more centralized schemes currently under consideration, and it would ensure institutional and professional accountability for the longitudinal quality management of clinical AI.

Indexed as

Artificial IntelligenceGovernment RegulationLaboratories, ClinicalQuality ImprovementHumansUnited Statesaccreditationartificial intelligencequality managementregulation

Identifiers

PMID39657218
PMCPMC11756634

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.