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AI integration in energy management: enhancing efficiency in Italian hospitals

Author

Listed:
  • Paolo Pariso

    (Università Degli Studi Della Campania, L. Vanvitelli “– Dipartimento di Ingegneria)

  • Michele Picariello

    (Università Degli Studi Della Campania, L. Vanvitelli “– Dipartimento di Ingegneria)

  • Alfonso Marino

    (Università Degli Studi Della Campania, L. Vanvitelli “– Dipartimento di Ingegneria)

Abstract

Background In 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. Methods A 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. Results The 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. Conclusions This 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.

Suggested Citation

  • Paolo Pariso & Michele Picariello & Alfonso Marino, 2025. "AI integration in energy management: enhancing efficiency in Italian hospitals," Health Economics Review, Springer, vol. 15(1), pages 1-10, December.
    • Handle: RePEc:spr:hecrev:v:15:y:2025:i:1:d:10.1186_s13561-025-00638-3
    DOI: 10.1186/s13561-025-00638-3
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