ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2013
Priority queuing models for hospital intensive care units and impacts to severe case patients.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Using queueing models as a decision support tool in allocating point-of-care HIV viral load testing machines in Kisumu County, Kenya.Health policy and planning · 2024Article
- Discrete-Event Simulation Modeling of Critical Care Flow: New Hospital, Old Challenges.Critical care explorations · 2020Article
- The self-regulating nature of occupancy in ICUs: stochastic homoeostasis.Health care management science · 2019Article
- Operations research in intensive care unit management: a literature review.Health care management science · 2018Review
- Rationale and methodology of a collaborative learning project in congenital cardiac care.American heart journal · 2016Review
- A Conceptual Framework for Improving Critical Care Patient Flow and Bed Use.Annals of the American Thoracic Society · 2015Article
- Application of Queuing Theory to Optimize the Triage Process in a Tertiary Emergency Care ("ER") Department.Journal of emergencies, trauma, and shockArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper examines several different queuing models for intensive care units (ICU) and the effects on wait times, utilization, return rates, mortalities, and number of patients served. Five separate intensive care units at an urban hospital are analyzed and distributions are fitted for arrivals and service durations. A system-based simulation model is built to capture all possible cases of patient flow after ICU admission. These include mortalities and returns before and after hospital exits. Patients are grouped into 9 different classes that are categorized by severity and length of stay (LOS). Each queuing model varies by the policies that are permitted and by the order the patients are admitted. The first set of models does not prioritize patients, but examines the advantages of smoothing the operating schedule for elective surgeries. The second set analyzes the differences between prioritizing admissions by expected LOS or patient severity. The last set permits early ICU discharges and conservative and aggressive bumping policies are contrasted. It was found that prioritizing patients by severity considerably reduced delays for critical cases, but also increased the average waiting time for all patients. Aggressive bumping significantly raised the return and mortality rates, but more conservative methods balance quality and efficiency with lowered wait times without serious consequences.
Indexed as
Identifiers
24551379PMC3900220What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.