ArticleHealth economics review2025
AI integration in energy management: enhancing efficiency in Italian hospitals.
Article in Health economics review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial Intelligence Platform Architecture for Hospital Systems: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Sustainable AI in medicine: navigating innovation, challenges, and environmental impact.Health economics review · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn the rapidly evolving healthcare landscape, artificial intelligence (AI) is revolutionizing hospital operations by enhancing operational efficiency and patient care. This study focuses on the integration of AI in energy management within Italian hospitals and the role of energy managers.
methodsA comprehensive questionnaire was developed to understand current practices, challenges, and opportunities in AI adoption within hospital energy management. The study targeted regions in Italy with the highest concentration of hospital energy managers. A quantitative approach was employed, and the collected data were statistically analysed for reliability and validity using SPSS.
resultsThe analysis revealed significant benefits of integrating AI in energy management, including optimized energy consumption, predictive maintenance, and greater sustainability. Energy managers' roles are evolving to leverage AI technologies effectively, ensuring compliance with energy regulations and promoting eco-friendly practices.
conclusionsThis research underscores AI's transformative potential in creating smarter, greener, and more efficient hospital environments. The findings highlight the importance of adopting AI-driven energy management solutions to enhance hospital efficiency. Future trends indicate further advancements in AI applications, necessitating ongoing adaptation and training for energy managers to exploit these technologies fully.
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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.