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Access Type

Open Access

Document Type

thesis

Degree Program

Industrial Engineering & Operations Research

Degree Type

Master of Science in Industrial Engineering and Operations Research (M.S.I.E.O.R.)

Year Degree Awarded

2013

Month Degree Awarded

September

Keywords

Hospital, admission, discharge, inpatient, discrete event simulation, waiting time

Abstract

Hospitals around the country are struggling to provide timely access to inpatient beds. We use discrete event simulation to study the inpatient admission and discharge processes in US hospitals. Demand for inpatient beds comes from two sources: the Emergency Department (ED) and elective surgeries (NonED). Bed request and discharge rates vary from hour to hour; furthermore, weekday demand is different from weekend demand. We use empirically collected data from national and local (Massachusetts) sources on different-sized community and referral hospitals, demand rates for ED and NonED patients, patient length of stay (LOS), and bed turnover times to calibrate our discrete event simulation model. In our computational experiments, we find that expanding hours of discharge, increasing the number of days elective patients are admitted in a week, and decreasing length of stay all showed statistically significant results in decreasing the average waiting time for patients. We discuss the implications of these results in practice, and list the key limitations of the model.

DOI

https://doi.org/10.7275/4497386

First Advisor

Hari J. Balasubramanian

Second Advisor

Philip A. Henneman

COinS