Evidence map›Paper›PMID 41654584›Full record

ReviewNPJ digital medicine2026

People process technology and operations framework for establishing AI governance in healthcare organizations.

Jee Young Kim, Alifia Hasan, Suresh Balu, Mark Sendak

Abstract readReview
In one paragraph

Review in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

4 authors.

Jee Young KimDuke Institute for Health Innovation, Durham, NC, USA. jee.young.kim@duke.edu.
Alifia HasanDuke Institute for Health Innovation, Durham, NC, USA.
Suresh Balu *Duke Institute for Health Innovation, Durham, NC, USA.
Mark Sendak *Duke Institute for Health Innovation, Durham, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AI governance ensures responsible use of AI through rules, processes, and technological tools. Implementing AI governance in healthcare delivery organizations (HDOs) requires understanding necessary capabilities and assessing readiness. This study introduces the scalable People, Process, Technology, and Operations (PPTO) framework-adapted from the People, Process, Technology (PPT) model-to guide governance across key domains. The PPTO framework offers a systematic roadmap for safe, effective, and equitable AI adoption in HDOs.

Identifiers

PMID41654584
PMCPMC12992770

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.