title: Priority queuing models for hospital intensive care units and impacts to severe case patients.
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.
authors.affiliation: Center for Operations Research in Medicine and HealthCare ; NSF I/UCRC Center for Health Organization Transformation ; College of Computing, Georgia Institute of Technology, Atlanta, GA;
authors.forename: Matthew S
authors.initials: MS
authors.lastname: Hagen
authors.affiliation: Emory Center for Critical Care, Emory University School of Medicine, Atlanta, GA.
authors.forename: Jeffrey K
authors.initials: JK
authors.lastname: Jopling
authors.affiliation: Emory Center for Critical Care, Emory University School of Medicine, Atlanta, GA.
authors.forename: Timothy G
authors.initials: TG
authors.lastname: Buchman
authors.affiliation: Center for Operations Research in Medicine and HealthCare ; NSF I/UCRC Center for Health Organization Transformation ; School of Industrial and Systems Engineering ; College of Computing, Georgia Institute of Technology, Atlanta, GA;
authors.forename: Eva K
authors.initials: EK
authors.lastname: Lee
mesh_terms: D001071:Appointments and Schedules; D057286:Electronic Health Records; D017052:Hospital Mortality; D006760:Hospitalization / Q000706:statistics & numerical data*; D006786:Hospitals, Urban / Q000458:organization & administration; D006801:Humans; D007362:Intensive Care Units / Q000458:organization & administration*; D007902:Length of Stay; D008962:Models, Theoretical; D009323:Natural Language Processing; D012720:Severity of Illness Index; D039061:Systematized Nomenclature of Medicine; D057188:Workflow