Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 1, 2025

Robotics in Surgery: A Modular Robotic Platform Driven Gastric Wedge Resection
07:27

Robotics in Surgery: A Modular Robotic Platform Driven Gastric Wedge Resection

Published on: February 7, 2025

417

Predicting Robotic Hysterectomy Incision Time: Optimizing Surgical Scheduling with Machine Learning.

Vaishali Shah1, Halley C Yung2, Jie Yang3

  • 1Department of Obstetrics and Gynecology, NYU Langone Health Grossman School of Medicine, New York, New York, USA. (Drs. V. Shah, Munoz, and Huang).

JSLS : Journal of the Society of Laparoendoscopic Surgeons
|January 20, 2025
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Missed opportunities: Germline testing following tumor sequencing.

Gynecologic oncology·2025
Same author

The missing data: A review of gender and sex disparities in research.

Cancer·2025
Same author

Diagnostic Modalities for Early Detection of Anastomotic Leak After Colorectal Surgery.

The Journal of surgical research·2024
Same author

Negative disease-related stigma 3-months after hemorrhagic stroke is related to functional outcome and female sex.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association·2024
Same author

A Rare Case of Uremic Optic Neuropathy Without Optic Disc Edema and With a Unique Imaging Correlate: Bilateral Diffusion Restriction of the Optic Nerves.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society·2023
Same author

Variations in the Branching Pattern and Course of the Left Axillary Artery: A Cadaveric Case Report.

Cureus·2023
This summary is machine-generated.

Machine learning accurately predicts robotic-assisted hysterectomy incision times, reducing operating room (OR) underutilization. This enhances surgical scheduling and hospital finances by optimizing OR use.

Area of Science:

  • Surgical Operations Research
  • Machine Learning in Healthcare
  • Health Systems Management

Background:

  • Operating room (OR) utilization is critical for hospital financial health.
  • Traditional surgical scheduling methods often lead to inefficient OR use.
  • Optimizing OR efficiency can significantly impact hospital revenue and cost management.

Purpose of the Study:

  • To develop a machine learning (ML) model for predicting incision times in robotic-assisted hysterectomies.
  • To improve the accuracy of surgical scheduling and enhance operating room utilization.
  • To identify key factors influencing surgical duration for better financial outcomes.

Main Methods:

  • A retrospective analysis of 2,702 robotic-assisted hysterectomies from January 2017 to April 2021 across three hospitals.
Keywords:
EfficiencyGynecologic surgical proceduresHysterectomyMachine learningOperative timeOrganizational

More Related Videos

A Teleoperated Robotic System-Assisted Percutaneous Transiliac-Transsacral Screw Fixation Technique
05:57

A Teleoperated Robotic System-Assisted Percutaneous Transiliac-Transsacral Screw Fixation Technique

Published on: January 6, 2023

2.2K
Robotic Taj Mahal Hepatectomy for Hilar Cholangiocarcinoma
09:19

Robotic Taj Mahal Hepatectomy for Hilar Cholangiocarcinoma

Published on: July 14, 2022

3.2K

Related Experiment Videos

Last Updated: Jun 1, 2025

Robotics in Surgery: A Modular Robotic Platform Driven Gastric Wedge Resection
07:27

Robotics in Surgery: A Modular Robotic Platform Driven Gastric Wedge Resection

Published on: February 7, 2025

417
A Teleoperated Robotic System-Assisted Percutaneous Transiliac-Transsacral Screw Fixation Technique
05:57

A Teleoperated Robotic System-Assisted Percutaneous Transiliac-Transsacral Screw Fixation Technique

Published on: January 6, 2023

2.2K
Robotic Taj Mahal Hepatectomy for Hilar Cholangiocarcinoma
09:19

Robotic Taj Mahal Hepatectomy for Hilar Cholangiocarcinoma

Published on: July 14, 2022

3.2K
  • Training and evaluation of five ML models, including an explainable boosting machine (EBM), using electronic medical record data.
  • Performance assessment via dynamic monthly updates and metrics like wait-time and excess-time blocks.

    • Main Results:

    • The EBM model demonstrated superior performance, significantly reducing excess-time blocks by approximately 52 hours over 51 months (P < .001).
    • The ML model improved prediction accuracy, classifying more surgeries within a 15% range of actual incision times.
    • Key predictors identified include surgeon experience, number of additional procedures, BMI, and uterine size.

    Conclusions:

    • Machine learning models can effectively predict surgical incision times for robotic-assisted hysterectomies.
    • Improved prediction accuracy leads to reduced OR underutilization and increased surgical throughput.
    • This approach offers a pathway to enhance hospital financial performance through optimized surgical scheduling.