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Poisson-stopped sum Lévy-type processes with application to stochastic modeling of hospital arrivals.

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Názov: Poisson-stopped sum Lévy-type processes with application to stochastic modeling of hospital arrivals.
Autori: Singh, Harpreet1 (AUTHOR), Ong, Seng Huat1,2 (AUTHOR), Ng, Choung Min1,3 (AUTHOR) ngcm@um.edu.my, Ratnavelu, Kurunathan4 (AUTHOR)
Zdroj: Communications in Statistics: Simulation & Computation. 2025, Vol. 54 Issue 11, p4712-4725. 14p.
Predmety: *STOCHASTIC models, *RESOURCE allocation, *HOSPITAL administration, *STOCHASTIC processes, LEVY processes, NEGATIVE binomial distribution, SKEWNESS (Probability theory)
Abstrakt: Patient arrivals at a hospital typically occur in clusters and the arrivals count data exhibits over-dispersion. To model these characteristics, the Lévy-type processes based on Poisson-stopped sum distributions are proposed as alternatives to the non-homogeneous Poisson process (NHPP), a popular model for hospital arrivals. The arrival rate for the NHPP is a deterministic function of time that does not account for arrivals in clusters while the genesis of Poisson-stopped sum distributions arises from modeling event clusters. Data on daily scheduled patient arrivals over 15-minute intervals collected from a Malaysian public hospital were used to illustrate the application of the Levy-type processes in healthcare management. It is shown that the proposed Lévy-type negative binomial and Lévy-type Thomas processes fit the data better than the NHPP. In addition, the Levy-type processes are computationally simpler and hence, it is envisaged that they will be potentially useful for implementation in staff scheduling and resource allocations. [ABSTRACT FROM AUTHOR]
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Databáza: Business Source Index
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Abstrakt:Patient arrivals at a hospital typically occur in clusters and the arrivals count data exhibits over-dispersion. To model these characteristics, the Lévy-type processes based on Poisson-stopped sum distributions are proposed as alternatives to the non-homogeneous Poisson process (NHPP), a popular model for hospital arrivals. The arrival rate for the NHPP is a deterministic function of time that does not account for arrivals in clusters while the genesis of Poisson-stopped sum distributions arises from modeling event clusters. Data on daily scheduled patient arrivals over 15-minute intervals collected from a Malaysian public hospital were used to illustrate the application of the Levy-type processes in healthcare management. It is shown that the proposed Lévy-type negative binomial and Lévy-type Thomas processes fit the data better than the NHPP. In addition, the Levy-type processes are computationally simpler and hence, it is envisaged that they will be potentially useful for implementation in staff scheduling and resource allocations. [ABSTRACT FROM AUTHOR]
ISSN:03610918
DOI:10.1080/03610918.2024.2391883