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Modelling, Analysis and Simulation of a Patient Admission Problem: A Social Network Approach

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1179))

Abstract

Due to pressing demand for the quality of care and to maximize the patient satisfaction, traditional scheduling may not cater the needs of patient’s accessibility for mitigating the patient tardiness and social effects. This paper addresses, patient appointment scheduling problem (PASP) in a radiology department in southern India, as a case study. Due to partial precedence constraints between different modalities, the problem is formulated as a static, multi-stage/multi-server system. We proposed a novel social network analysis (SNA) based approach to examine the relationship between identified modalities and their influence with different examination type. To validate the results of SNA model, in a real time environment a simulation analysis is carried out by using FlexSim Healthcare software. Based on the empirical data collected from the radiology department, comparisons between the present condition of the department and the achieved results from proposed approach is performed through discrete event simulation model. The results indicate that the proposed approach has proved its effectiveness on the system performance by reducing the average total completion time of the system by 5% and 38% in patients waiting time.

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Correspondence to Vijayakumar Manupati .

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Ramakurthi, V.B., Manupati, V., Panigrahi, S., Varela, M.L.R., Putnik, G., Bose, P.S.C. (2021). Modelling, Analysis and Simulation of a Patient Admission Problem: A Social Network Approach. In: Abraham, A., Shandilya, S., Garcia-Hernandez, L., Varela, M. (eds) Hybrid Intelligent Systems. HIS 2019. Advances in Intelligent Systems and Computing, vol 1179. Springer, Cham. https://doi.org/10.1007/978-3-030-49336-3_5

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