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 Videos

Optimizing admissions to an intensive care unit.

Amir Shmueli1, Charles L Sprung, Edward H Kaplan

  • 1Department of Health Management. School of Public Health, The Hebrew University of Jerusalem, P.O. Box 12272, Jerusalem 91120, Israel. ashmueli@md.huji.ac.il

Health Care Management Science
|August 29, 2003
PubMed
Summary
This summary is machine-generated.

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

End-of-life decision-making in very old critically ill patients.

European geriatric medicine·2026
Same author

Is informed consent in the critically ill informed?

Minerva anestesiologica·2026
Same author

Influence of Age in End-of-Life Practices in Worldwide ICUs (ETHICUS-2): A Prospective Observational Study.

Critical care medicine·2026
Same author

Executive Summary: Society of Critical Care Medicine Guidelines for the Allocation of Critical Care Resources to Adults During Crisis-Level Shortages.

Critical care medicine·2026
Same author

Society of Critical Care Medicine Guidelines for the Allocation of Critical Care Resources to Adults During Crisis-Level Shortages.

Critical care medicine·2026
Same author

Incentives and Equity: A Randomized Controlled Trial to Improve Glycemic Control in Socioeconomically Disadvantaged Patients With Diabetes.

Annals of family medicine·2026

Optimizing intensive care unit (ICU) admissions can save lives. A new model shows that prioritizing patients with a survival benefit of at least 19.4% could save 18 more lives annually compared to standard policies.

Area of Science:

  • Healthcare Management
  • Operations Research
  • Critical Care Medicine

Background:

  • Intensive care units (ICUs) face challenges in optimizing patient admissions to maximize life-saving impact.
  • Queueing theory provides a framework for modeling patient flow and resource allocation in critical care settings.

Purpose of the Study:

  • To develop and evaluate a model for optimizing ICU admissions to maximize the expected number of lives saved.
  • To compare the effectiveness of different admission policies, including First Come First Served (FCFS), FCFS with a hurdle (FCFS-H), and FCFS with a bed-specific hurdle (FCFS-BSH).

Main Methods:

  • Utilized queueing theory to model the probability distribution of occupied ICU beds.
  • Applied the model to patient referral data from a specific hospital ICU.

Related Experiment Videos

  • Statistically estimated the distribution of expected incremental survival benefits for referred patients.
  • Main Results:

    • Implementing an FCFS-H policy with a 19.4% survival benefit threshold could save an additional 18 statistical lives annually (17.9% improvement) compared to FCFS.
    • The FCFS-BSH policy offered a marginal additional benefit of 1.4 statistical lives annually (1.2% improvement) over FCFS-H.

    Conclusions:

    • Optimizing ICU admissions based on predicted survival benefits can significantly increase lives saved.
    • A hurdle-based admission policy demonstrates superior effectiveness in maximizing life-saving potential within ICUs.