Literature DB >> 31823034

Artificial Intelligence: A New Tool in Operating Room Management. Role of Machine Learning Models in Operating Room Optimization.

Valentina Bellini1, Marco Guzzon2, Barbara Bigliardi2, Monica Mordonini2, Serena Filippelli2, Elena Bignami3.   

Abstract

We conducted a systematic review of literature to better understand the role of new technologies in the perioperative period; in particular we focus on the administrative and managerial Operating Room (OR) perspective. Studies conducted on adult (≥ 18 years) patients between 2015 and February 2019 were deemed eligible. A total of 19 papers were included. Our review suggests that the use of Machine Learning (ML) in the field of OR organization has many potentials. Predictions of the surgical case duration were obtain with a good performance; their use could therefore allow a more precise scheduling, limiting waste of resources. ML is able to support even more complex models, which can coordinate multiple spaces simultaneously, as in the case of the post-anesthesia care unit and operating rooms. Types of Artificial Intelligence could also be used to limit another organizational problem, which has important economic repercussions: cancellation. Random Forest has proven effective in identifing surgeries with high risks of cancellation, allowing to plan preventive measures to reduce the cancellation rate accordingly. In conclusion, although data in literature are still limited, we believe that ML has great potential in the field of OR organization; however, further studies are needed to assess the effective role of these new technologies in the perioperative medicine.

Entities:  

Keywords:  Anesthesia; Artificial intelligence; Big data; Block time; Hospital administration; Machine learning; Operating room; Operating room efficiency; Perioperative; Recovery room; Robotic assisted surgery; Scheduling

Mesh:

Year:  2019        PMID: 31823034     DOI: 10.1007/s10916-019-1512-1

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  33 in total

1.  A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models.

Authors:  Evangelia Christodoulou; Jie Ma; Gary S Collins; Ewout W Steyerberg; Jan Y Verbakel; Ben Van Calster
Journal:  J Clin Epidemiol       Date:  2019-02-11       Impact factor: 6.437

Review 2.  Machine Learning in Medicine.

Authors:  Alvin Rajkomar; Jeffrey Dean; Isaac Kohane
Journal:  N Engl J Med       Date:  2019-04-04       Impact factor: 91.245

3.  Automatic Localization of the Needle Target for Ultrasound-Guided Epidural Injections.

Authors:  Mehran Pesteie; Victoria Lessoway; Purang Abolmaesumi; Robert N Rohling
Journal:  IEEE Trans Med Imaging       Date:  2017-08-11       Impact factor: 10.048

4.  Improving Operating Room Efficiency, Part 1: General Managerial and Preoperative Strategies.

Authors:  Travis Healey; Mouhanad M El-Othmani; Jessica Healey; Todd C Peterson; Khaled J Saleh
Journal:  JBJS Rev       Date:  2015-10-20

Review 5.  Efficiency improvement in the operating room.

Authors:  Abigail J Fong; Meghan Smith; Alexander Langerman
Journal:  J Surg Res       Date:  2016-04-29       Impact factor: 2.192

6.  Clinical Proof-of-concept of a Novel Platform Utilizing Biopsy-derived Live Single Cells, Phenotypic Biomarkers, and Machine Learning Toward a Precision Risk Stratification Test for Prostate Cancer Grade Groups 1 and 2 (Gleason 3 + 3 and 3 + 4).

Authors:  David Albala; Michael S Manak; Jonathan S Varsanik; Hani H Rashid; Vladimir Mouraviev; Stephen M Zappala; Ene Ette; Naveen Kella; Kimberly M Rieger-Christ; Grannum R Sant; Ashok C Chander
Journal:  Urology       Date:  2018-10-10       Impact factor: 2.649

7.  Predicting the Future - Big Data, Machine Learning, and Clinical Medicine.

Authors:  Ziad Obermeyer; Ezekiel J Emanuel
Journal:  N Engl J Med       Date:  2016-09-29       Impact factor: 91.245

8.  Medical big data: promise and challenges.

Authors:  Choong Ho Lee; Hyung-Jin Yoon
Journal:  Kidney Res Clin Pract       Date:  2017-03-31

9.  Machine learning in medicine: a practical introduction.

Authors:  Jenni A M Sidey-Gibbons; Chris J Sidey-Gibbons
Journal:  BMC Med Res Methodol       Date:  2019-03-19       Impact factor: 4.615

10.  A Quantile Regression Approach to Estimating the Distribution of Anesthetic Procedure Time during Induction.

Authors:  Hsin-Lun Wu; Wen-Kuei Chang; Ken-Hua Hu; Richard M Langford; Mei-Yung Tsou; Kuang-Yi Chang
Journal:  PLoS One       Date:  2015-08-04       Impact factor: 3.240

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  7 in total

1.  Opportunities and challenges of artificial intelligence in the medical field: current application, emerging problems, and problem-solving strategies.

Authors:  Lushun Jiang; Zhe Wu; Xiaolan Xu; Yaqiong Zhan; Xuehang Jin; Li Wang; Yunqing Qiu
Journal:  J Int Med Res       Date:  2021-03       Impact factor: 1.671

2.  Key Experimental Factors of Machine Learning-Based Identification of Surgery Cancellations.

Authors:  Fengyi Zhang; Xinyuan Cui; Renrong Gong; Chuan Zhang; Zhigao Liao
Journal:  J Healthc Eng       Date:  2021-02-20       Impact factor: 2.682

Review 3.  Artificial intelligence in thoracic surgery: a narrative review.

Authors:  Valentina Bellini; Marina Valente; Paolo Del Rio; Elena Bignami
Journal:  J Thorac Dis       Date:  2021-12       Impact factor: 2.895

4.  Machine Learning-Based Models Predicting Outpatient Surgery End Time and Recovery Room Discharge at an Ambulatory Surgery Center.

Authors:  Rodney A Gabriel; Bhavya Harjai; Sierra Simpson; Nicole Goldhaber; Brian P Curran; Ruth S Waterman
Journal:  Anesth Analg       Date:  2022-04-07       Impact factor: 6.627

5.  Estimation of Surgery Durations Using Machine Learning Methods-A Cross-Country Multi-Site Collaborative Study.

Authors:  Sean Shao Wei Lam; Hamed Zaribafzadeh; Boon Yew Ang; Wendy Webster; Daniel Buckland; Christopher Mantyh; Hiang Khoon Tan
Journal:  Healthcare (Basel)       Date:  2022-06-25

Review 6.  Artificial intelligence and anesthesia: a narrative review.

Authors:  Valentina Bellini; Emanuele Rafano Carnà; Michele Russo; Fabiola Di Vincenzo; Matteo Berghenti; Marco Baciarello; Elena Bignami
Journal:  Ann Transl Med       Date:  2022-05

7.  Role of Intelligent Management Systems in Surgical Punctuality and Quality of Care.

Authors:  Gendi Li; Shenhui Huang
Journal:  Comput Intell Neurosci       Date:  2022-10-11
  7 in total

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