Evidence map›Paper›PMID 42736977›Full record

ArticleHealthcare (Basel, Switzerland)2026

Economic Factors Associated with AI Adoption in Oncology: Cost-Effectiveness Perceptions, Reimbursement Readiness, and Return-on-Investment Confidence Among Romanian Healthcare Professionals.

Dragoș-Ciprian Negoiță, Livia Stanga, Horia Silviu Branea, Ciprian Ilie Roșca, Adrian Cosmin Ilie, Ovidiu Rosca

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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5 · Who and what money

Authors and funding

6 authors.

Dragoș-Ciprian NegoițăDoctoral School, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy Timisoara, Eftimie Murgu Square 2, 300041 Timisoara, Romania.
Livia StangaDiscipline of Microbiology, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania.
Horia Silviu BraneaDepartment of Internal Medicine I-Medical Semiotics II, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania.ORCID 0000-0002-7896-1253
Ciprian Ilie RoșcaDepartment V, Internal Medicine I-Discipline of Medical Semiology I, Center of Advanced Research in Cardiology and Hemostaseology, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania.ORCID 0000-0002-8619-0479
Adrian Cosmin IlieDepartment of Functional Sciences, Discipline of Public Health, Center for Translational Research and Systems Medicine, "Victor Babes" University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania.
Ovidiu RoscaDepartment of Infectious Diseases, "Victor Babes" University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania.ORCID 0000-0001-8236-2205

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesArtificial intelligence (AI) tools promise efficiency gains in oncology, yet adoption depends on economic factors that remain under-characterized in Eastern European health systems. We quantified AI economic literacy, cost-effectiveness perceptions, reimbursement readiness, and return-on-investment (ROI) confidence among Romanian oncology professionals; we described candidate economic adoption profiles and examined whether sector was associated with the strength of the indirect association between literacy and willingness to invest via ROI confidence. MATERIALS AND

methodsA multicenter cross-sectional survey (

resultsMean age was 41.3 ± 10.7 years; 58.3% were female. AIELI was moderate (13.7 ± 4.6/25). Familiarity favored cost-effectiveness analysis (59.3%) over AI-specific reimbursement codes (16.7%). High willingness to invest occurred in 48.1% and was independently associated with higher AIELI (aOR 1.78 per +1 SD; 95% CI 1.17-2.71), higher ROI confidence (aOR 1.93; 1.24-3.02), lower perceived financial barriers (aOR 0.58; 0.37-0.91), and prior AI training (aOR 2.34; 1.13-4.86). Three exploratory profiles were identified: Cost-Conscious Adopters (

conclusionsIn this exploratory cross-sectional sample, AI economic literacy and ROI confidence were associated with willingness to invest in oncology AI, interpreted as stated support for investment rather than an enacted procurement decision, since many respondents lacked formal budgetary authority. Because the design cannot establish temporal ordering, whether sector-tailored capability-building and reimbursement clarity would increase adoption remains a hypothesis for prospective evaluation.

Indexed as

artificial intelligencecost–benefit analysishealthcare economics and organizationsmedical oncologyreimbursement mechanisms

Identifiers

PMID42736977
PMCPMC13565732

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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.