title: A cost sensitive inpatient bed reservation approach to reduce emergency department boarding times.
abstract: Emergency departments (ED) in hospitals are experiencing severe crowding and prolonged patient waiting times. A significant contributing factor is boarding delays where admitted patients are held in ED (occupying critical resources) until an inpatient bed is identified and readied in the admit wards. Recent research has suggested that if the hospital admissions of ED patients can be predicted during triage or soon after, then bed requests and preparations can be triggered early on to reduce patient boarding time. We propose a cost sensitive bed reservation policy that recommends optimal bed reservation times for patients. The policy relies on a classifier that estimates the probability that the ED patient will be admitted using the patient information collected and readily available at triage or right after. The policy is cost sensitive in that it accounts for costs associated with patient admission prediction misclassification as well as costs associated with incorrectly selecting the reservation time. Results from testing the proposed bed reservation policy using data from a VA Medical Center are very promising and suggest significant cost saving opportunities and reduced patient boarding times.
authors.affiliation: Industrial & Systems Engineering Department, Wayne State University, Detroit, MI, 48202, USA.
authors.forename: Shanshan
authors.initials: S
authors.lastname: Qiu
authors.forename: Ratna Babu
authors.initials: RB
authors.lastname: Chinnam
authors.forename: Alper
authors.initials: A
authors.lastname: Murat
authors.forename: Bassam
authors.initials: B
authors.lastname: Batarse
authors.forename: Hakimuddin
authors.initials: H
authors.lastname: Neemuchwala
authors.forename: Will
authors.initials: W
authors.lastname: Jordan
mesh_terms: D003365:Costs and Cost Analysis; D003441:Crowding; D017598:Efficiency, Organizational; D004636:Emergency Service, Hospital / Q000458:organization & administration*; D006801:Humans; D015233:Models, Statistical; D010343:Patient Admission / Q000191:economics* / Q000706:statistics & numerical data*; D011336:Probability; D013997:Time Factors; D014218:Triage / Q000458:organization & administration* / Q000706:statistics & numerical data*; D014481:United States; D014493:United States Department of Veterans Affairs / Q000458:organization & administration / Q000706:statistics & numerical data; D014850:Waiting Lists