ArticleHealth care management science2025
The crucial role of explainable artificial intelligence (XAI) in improving health care management.
Article in Health care management science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Use of Machine Learning in Emergency Care Units: A Systematic Review.Journal of primary care & community healthPooled it
- AI Trustworthiness in the Perioperative Period for Patients with Serious Illness: Scoping Narrative Review.JMIR perioperative medicine · 2026Article
- A lifecycle governance and learning health system framework for trustworthy, generalizable, and sustainable human-ai partnership in clinical practice: Lessons from the asthma-guidance and prediction system (A-GPS).Journal of the National Medical Association · 2026Review
- Advances in mosquito-borne disease surveillance using machine learning.New microbes and new infections · 2026Article
- Integrative Transcriptomic and Machine Learning Analysis of ecDNA-Associated Features for Studying Chemotherapy Resistance in TNBC.bioRxiv : the preprint server for biology · 2026Article
- A comprehensive review of explainable artificial intelligence in healthcare methods, evaluation, and clinical integration.iScience · 2026Review
- Explainable Artificial Intelligence in Healthcare: Current Landscape, Challenges, and Future Directions.Health science reports · 2026Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This current opinion explores the transformative potential of explainable artificial intelligence (XAI) for health care management systems. While AI has already demonstrated substantial benefits in clinical decision-making, operational efficiency and patient outcomes, its adoption is often hindered by the lack of transparency in AI-driven decision-making. XAI bridges this gap by providing interpretability, thereby increasing trust between policy-makers, clinicians, administrators and patients. However, despite promising examples, the explicit integration of XAI remains underexplored in health care management research. This current opinion therefore aims to emphasize the crucial role of XAI in improving health care management and to position it as an important topic for advancing the field, with Health Care Management Science (HCMS) playing a leadership role in fostering this development.
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What OpenQuestion holds
Registered trials
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.