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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
Included in
Health and Medical Administration Commons, Industrial Engineering Commons, Operational Research Commons