Evidence map›Paper›PMID 42852069›Full record

ArticleHealth affairs scholar2026

Private equity ownership and artificial intelligence adoption by hospitals in the United States.

Rocco Friebel, Daniel Arnold, Michael Anderson, Jonathan Cantor, Yashaswini Singh

Abstract read
In one paragraph

Article in Health affairs scholar, 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

5 authors.

Rocco FriebelDepartment of Health Policy, The London School of Economics and Political Science, Houghton Street, London WC2A 2AE, United Kingdom.ORCID https://orcid.org/0000-0003-1256-9096
Daniel ArnoldDepartment of Health Services, Policy, and Practice, Brown University, 121 S Main Street, Providence, RI 02903, United States.ORCID https://orcid.org/0000-0001-9969-8389
Michael AndersonLSE Health, The London School of Economics and Political Science, Houghton Street, London WC2A 2AE, United Kingdom.ORCID https://orcid.org/0000-0002-8454-4640
Jonathan CantorRAND Corporation, 1778 Main Street, Santa Monica, CA 90401, United States.ORCID https://orcid.org/0000-0003-4468-833X
Yashaswini SinghDepartment of Health Services, Policy, and Practice, Brown University, 121 S Main Street, Providence, RI 02903, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Private equity (PE) firms own a growing share of United States hospitals and claim that capital infusions support technology investment. We examined the association between PE hospital ownership and the likelihood of artificial intelligence (AI) technology adoption. Methods: We linked the 2024 American Hospital Association Annual Survey to a database of PE acquisitions and exits. Mixed-effects logistic models estimated any, clinical, and operational AI adoption by hospital ownership type, adjusting for hospital and market characteristics. In secondary analyses, we examined challenges to AI implementation. Results: PE-owned hospitals had higher adjusted adoption of any AI (difference, 24.5 percentage points; 95% confidence interval, 11.2 to 37.8) and clinical AI (difference, 27.5 percentage points; 95% confidence interval, 14.0 to 41.1) than other for-profit hospitals but did not differ from not-for-profit hospitals. Operational adoption did not differ by ownership. In secondary analyses, not-for-profit hospitals reported any, cost and resource, and regulatory and safety challenges more often than PE-owned hospitals; PE-owned hospitals reported staff-training challenges more often than other for-profit hospitals. Conclusion: PE-owned and not-for-profit hospitals had similar adoption of any and clinical AI, and both exceeded other for-profit hospitals, consistent with a capital access advantage that does not extend to the broader for-profit sector.

Indexed as

artificial intelligencehospital ownershipprivate equitytechnology adoption

Identifiers

PMID42852069
PMCPMC13648208

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.