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: May 13, 2026

A Recovery Cardiopulmonary Bypass Model Without Transfusion or Inotropic Agents in Rats
09:54

A Recovery Cardiopulmonary Bypass Model Without Transfusion or Inotropic Agents in Rats

Published on: March 23, 2018

Recovery bed planning in cardiovascular surgery: a simulation case study.

Yariv N Marmor1, Thomas R Rohleder, David J Cook

  • 1Mayo Clinic, Department of Health Sciences Research, Center for the Science of Health Care Delivery, 200 1st Street SW, Rochester, MN, 55905, USA.

Health Care Management Science
|March 20, 2013
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

Cardiomyopathy VII: Pre and Post Operative Nursing Management01:28

Cardiomyopathy VII: Pre and Post Operative Nursing Management

Patients with hypertrophic cardiomyopathy (HCM) and left ventricular outflow tract (LVOT) obstruction who remain symptomatic despite optimal medical therapy may undergo a septal myectomy (Morrow procedure). This procedure involves excising a portion of the hypertrophied septum below the aortic valve using a heart-lung machine to improve blood flow through the LVOT. Effective preoperative and postoperative nursing management ensures successful patient outcomes, minimizes complications, and...

You might also read

Related Articles

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

Sort by
Same author

Complete Acid-Based Hydrolysis Assay for Carbohydrate Quantification in Seaweed: A Species-Specific Optimized Approach.

Methods in molecular biology (Clifton, N.J.)·2026
Same author

Contrastive learning enhances fairness in pathology artificial intelligence systems.

Cell reports. Medicine·2025
Same author

Primary Merkel Cell Carcinoma of the Deep Breast Parenchyma.

International journal of surgical pathology·2025
Same author

Uncertainty-aware ensemble of foundation models differentiates glioblastoma from its mimics.

Nature communications·2025
Same author

Well-Defined Amylose Acetate-<i>graft</i>-polylactide Graft Polymers as Compatibilizers for Renewable Polymer Blends.

Biomacromolecules·2025
Same author

Incorporating Machine Learning Driven Factors in the Design of Electronic-triggers to Detect Diagnostic Errors in the Emergency Department.

Journal of patient safety·2025

This study developed a simulation model to optimize hospital bed management for cardiovascular surgery patients. The model projected a 30% reduction in required beds, improving resource allocation and patient care.

Area of Science:

  • Healthcare Operations Research
  • Hospital Resource Management
  • Cardiovascular Surgery Patient Flow

Background:

  • Recovery beds in intensive care units (ICU) and progressive care units (PCU) represent significant hospital costs.
  • Effective management of these critical resources is essential for maintaining high patient service levels.

Purpose of the Study:

  • To develop and implement a discrete-event simulation model for predicting minimum bed requirements for cardiovascular surgical patients.
  • To assess the impact of operational changes, such as surgery schedule smoothing and patient transfers, on bed needs.

Main Methods:

  • Development of a discrete-event simulation model tailored to Mayo Clinic's recovery bed needs.
  • Incorporation of factors like surgical growth, new recovery protocols, and patient transfer strategies into the model.

Related Experiment Videos

Last Updated: May 13, 2026

A Recovery Cardiopulmonary Bypass Model Without Transfusion or Inotropic Agents in Rats
09:54

A Recovery Cardiopulmonary Bypass Model Without Transfusion or Inotropic Agents in Rats

Published on: March 23, 2018

  • Analysis of simulation outputs to determine optimal bed allocation and operational adjustments.

    • Main Results:

    • The simulation model projected a 30% lower bed requirement compared to traditional bed-planning methods.
    • Exploring options like smoothing surgery schedules and transferring long-stay ICU patients demonstrated potential for substantial bed reduction.
    • The model provided data-driven insights for effective hospital resource management.

    Conclusions:

    • Discrete-event simulation is a valuable tool for optimizing hospital bed management in cardiovascular surgery.
    • Operational adjustments can significantly decrease the number of required recovery beds, leading to cost savings and improved efficiency.
    • The developed model supports achieving high patient service levels while minimizing resource utilization.