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医院管理软件系统的动态行为与元启发式优化

Dynamical behaviour and meta heuristic optimization of a hospital management software system.

作者信息

Harini R, Indhira K

机构信息

Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore - 632 014, Tamil Nadu, India.

出版信息

Heliyon. 2024 Aug 12;10(16):e35937. doi: 10.1016/j.heliyon.2024.e35937. eCollection 2024 Aug 30.

Abstract

The growing demand for easily available healthcare in recent years has fuelled the digitization of healthcare services. The Hospital Management System (HMS) software stands out as a comprehensive solution among the software systems and tools that hospitals and clinics are developing in tandem with this trend. In order to effectively manage many facets of hospital operations, in this paper, we propose an approach for investigating software of this kind. Thus, we characterise the HMS software as a unique sort of batch arrival retrial queueing system (QS) that can handle both ordinary and priority patient demands. Furthermore, it permits patient resistance (balk) and departure (renege) in specific circumstances. The proposed model is additionally deployed within the framework of Bernoulli working vacation. The supplementary variable technique (SVT) has been utilised to obtain the necessary results. ANFIS, a soft computing tool, is used to validate the analytical results as well. Finally, this study seeks to enhance the cost-effectiveness of software creation by employing four unique optimization methods, aiming to achieve optimal efficiency in resource utilization.

摘要

近年来,对便捷医疗服务的需求不断增长,推动了医疗服务的数字化。在医院和诊所顺应这一趋势开发的软件系统和工具中,医院管理系统(HMS)软件脱颖而出,成为一种全面的解决方案。为了有效管理医院运营的多个方面,在本文中,我们提出了一种研究此类软件的方法。因此,我们将HMS软件描述为一种独特的批量到达重试排队系统(QS),它可以处理普通患者需求和优先患者需求。此外,它允许患者在特定情况下拒绝(犹豫)和离开(中途退出)。所提出的模型还部署在伯努利工作休假的框架内。已使用补充变量技术(SVT)来获得必要的结果。还使用了一种软计算工具自适应神经模糊推理系统(ANFIS)来验证分析结果。最后,本研究旨在通过采用四种独特的优化方法来提高软件创建的成本效益,旨在实现资源利用的最佳效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1eed/11379607/107df428efa7/gr001.jpg

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