Markov chain analysis for the neonatal inpatient flow in a hospital

Yuta Kanai () and Hideaki Takagi ()
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Yuta Kanai: Tsukuba Institute of Research
Hideaki Takagi: University of Tsukuba (Professor Emeritus)

Health Care Management Science, 2021, vol. 24, issue 1, No 6, 92-116

Abstract: Abstract Discrete-time Markov chain and queueing-theoretic models are used to quantitatively formulate the flow of neonatal inpatients over several wards in a hospital. Parameters of the models are determined from the operational analysis of the record of the numbers of admission/departure for each ward every day and the order log of patient movement from ward to ward for two years provided by the Medical Information Department of the University of Tsukuba Hospital in Japan. Our formulation is based on the analysis of the precise routes (the route of an inpatient is defined as a sequence of the wards in which he/she stays from admission to discharge) and their length-of-stay (LoS) in days in each ward on their routes for all neonatal inpatients. Our theoretical model calculates the probability distribution for the number of patients staying in each ward per day which agrees well with the corresponding histogram observed for each ward as well as for the whole hospital. The proposed method can be used for the long-term capacity planning of hospital wards with respect to the probabilistic bed utilization.

Keywords: Hospital capacity planning; Bed utilization; Neonatal patient flow; Patient-days; Operations research; Markov chain; Queueing theory; Poisson process; 60J20; 62P10; 92C50 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10729-020-09515-3

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