Artificial Intelligence in Operating Room Management.

This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected studies from February 2019 to September 2023 are analyzed. The review emphasizes the significant impact of AI on predicting surgical...

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Publicado en:Journal of Medical Systems Vol. 48; no. 1; pp. 1 - 17
Autores principales: Bellini, Valentina, Russo, Michele, Domenichetti, Tania, Panizzi, Matteo, Allai, Simone, Bignami, Elena Giovanna
Formato: research systematic review tables/charts Journal Article
Publicado: Springer Nature 2/14/2024
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 2/14/2024
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-024-02038-2
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          Bellini, Valentina
          Russo, Michele
          Domenichetti, Tania
          Panizzi, Matteo
          Allai, Simone
          Bignami, Elena Giovanna
        affil: https://ror.org/02k7wn190 Anesthesiology, Intensive Care and Pain Medicine Division, Department of Medicine and Surgery, University of Parma, 43126, Parma, Italy
      sug:
        subj:
          Operating Rooms Administration
          Machine Learning Utilization
          Health Resource Allocation
          Post Anesthesia Care Units
          Surgery Cancellations
          Treatment Duration Evaluation
          Prediction Models
          Perioperative Care
          Human
          Systematic Review
          Adult
          PubMed
          Embase
          Descriptive Statistics
          Linear Regression
          Confidence Intervals
          Logistic Regression
          Machine Learning
          Neural Networks (Computer)
          Length of Stay
          Decision Making
          Artificial Intelligence Utilization
          Adult: 19-44 years
      ab: This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected studies from February 2019 to September 2023 are analyzed. The review emphasizes the significant impact of AI on predicting surgical case durations, optimizing post-anesthesia care unit resource allocation, and detecting surgical case cancellations. Machine learning algorithms such as XGBoost, random forest, and neural networks have demonstrated their effectiveness in improving prediction accuracy and resource utilization. However, challenges such as data access and privacy concerns are acknowledged. The review highlights the evolving nature of artificial intelligence in perioperative medicine research and the need for continued innovation to harness artificial intelligence's transformative potential for healthcare administrators, practitioners, and patients. Ultimately, artificial intelligence integration in operative room management promises to enhance healthcare efficiency and patient outcomes.
      pubtype: Academic Journal
      doctype:
        research
        systematic review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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