Evidence map›Paper›PMID 38449840›Full record

ReviewHealth services research and managerial epidemiology

Artificial Intelligence and Decision-Making in Healthcare: A Thematic Analysis of a Systematic Review of Reviews.

Mohsen Khosravi, Zahra Zare, Seyyed Morteza Mojtabaeian, Reyhane Izadi

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Health services research and managerial epidemiology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed, 6 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

137 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Detection of parkinson's disease with neuroimaging modalities using machine learning and artificial intelligence: a systematic review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
    Pooled it
  3. Digital health tools in the management of allergic rhinitis: a systematic review.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2025
    Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Trial
  8. Trial
  9. Trial
  10. Article
  11. Review
  12. Review
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

77 more citing papers are in PubMed but not listed here.

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.

Mohsen KhosraviDepartment of Health Care Management, School of Management and Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.ORCID https://orcid.org/0000-0002-0576-7660
Zahra ZareDepartment of Health Care Management, School of Management and Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.
Seyyed Morteza MojtabaeianDepartment of Healthcare Economics, School of Management and Medical Informatics, Shiraz University of Medical Sciences, Shiraz, Iran.
Reyhane IzadiDepartment of Health Care Management, School of Management and Information Sciences, Shiraz University of Medical Sciences, Shiraz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The use of artificial intelligence (AI), which can emulate human intelligence and enhance clinical results, has grown in healthcare decision-making due to the digitalization effects and the COVID-19 pandemic. The purpose of this study was to determine the scope of applications of AI tools in the decision-making process in healthcare service delivery networks. Materials and methods: This study used a qualitative method to conduct a systematic review of the existing reviews. Review articles published between 2000 and 2024 in English-language were searched in PubMed, Scopus, ProQuest, and Cochrane databases. The CASP (Critical Appraisal Skills Programme) Checklist for Systematic Reviews was used to evaluate the quality of the articles. Based on the eligibility criteria, the final articles were selected and the data extraction was done independently by 2 authors. Finally, the thematic analysis approach was used to analyze the data extracted from the selected articles. Results: Of the 14 219 identified records, 18 review articles were eligible and included in the analysis, which covered the findings of 669 other articles. The quality assessment score of all reviewed articles was high. And, the thematic analysis of the data identified 3 main themes including clinical decision-making, organizational decision-making, and shared decision-making; which originated from 8 subthemes. Conclusions: This study revealed that AI tools have been applied in various aspects of healthcare decision-making. The use of AI can improve the quality, efficiency, and effectiveness of healthcare services by providing accurate, timely, and personalized information to support decision-making. Further research is needed to explore the best practices and standards for implementing AI in healthcare decision-making.

Indexed as

artificial intelligencedecision makinghealthcare systemhealth servicesthematic analysis

Identifiers

PMID38449840
PMCPMC10916499

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.