Evidence map›Paper›PMID 39351313›Full record

ArticleDigital health

How can physicians adopt AI-based applications in the United Arab Emirates to improve patient outcomes?

Tarek Mansour, Markus Bick

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Between Hope and Skepticism: Parent and Provider Expectations of Artificial Intelligence as a Bridge to Human-Centered Care for Children With Chronic Illness.Health expectations : an international journal of public participation in health care and health policy · 2026
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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

2 authors.

Tarek MansourESCP Business School, Paris, France.ORCID https://orcid.org/0000-0002-4353-9124
Markus BickESCP Business School, Information & Operations Management, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The enabling and derailing factors for using artificial intelligence (AI)-based applications to improve patient care in the United Arab Emirates (UAE) from the physicians' perspective are investigated. Factors to accelerate the adoption of AI-based applications in the UAE are identified to aid implementation. Methods: A qualitative, inductive research methodology was employed, utilizing semi-structured interviews with 12 physicians practicing in the UAE. The collected data were analyzed using NVIVO software and grounded theory was used for thematic analysis. Results: This study identified factors specific to the deployment of AI to transform patient care in the UAE. First, physicians must control the applications and be fully trained and engaged in the testing phase. Second, healthcare systems need to be connected, and the AI outcomes need to be easily interpretable by physicians. Third, the reimbursement for AI-based applications should be settled by insurance or the government. Fourth, patients should be aware of and accept the technology before physicians use it to avoid negative consequences for the doctor-patient relationship. Conclusions: This research was conducted with practicing physicians in the UAE to determine their understanding of enabling and derailing factors for improving patient care through AI-based applications. The importance of involving physicians as the accountable agents for AI tools is highlighted. Public awareness regarding AI in healthcare should be improved to drive public acceptance.

Indexed as

AI applicationsArtificial intelligencedigital healthgeneralhealthcarehealthcare managementpatient care

Identifiers

PMID39351313
PMCPMC11440542

What OpenQuestion holds

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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.