An application of optimal control in medical systems: optimal investment strategy in doctors.

IF 2 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Network Modeling and Analysis in Health Informatics and Bioinformatics Pub Date : 2023-01-01 DOI:10.1007/s13721-022-00408-9

Mustafa Akan, Ebru Geçici

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Abstract

Health care is ever more important with the aging population and with the increased awareness of the importance of the medical systems due to the corona crisis that showed the capacity of the health care infrastructure, especially in terms of numbers of health care personnel such as doctors, was not sufficient. Assuming that the number of doctors per patient is one of the determinants of patient satisfaction, optimal investments in new doctors, specialist doctors and foreign doctors are analyzed. Optimal Control Theory is employed to determine the optimal investment strategy for new doctors (new graduates), specialists and foreign doctors to maximize the net (of costs) patient satisfaction over a fixed time horizon. It is found that a nation with an insufficient number of total doctors and specialist doctors at the beginning of the planning horizon should increase the investment in new doctors as a quadratic function of time, increase the local specialist doctors linearly, while employing foreign doctors as to equate their cost to the marginal satisfaction of patients.

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最优控制在医疗系统中的应用:医生的最优投资策略。

随着人口老龄化和冠状病毒危机对医疗系统重要性的认识日益提高，卫生保健变得越来越重要，这表明卫生保健基础设施的能力，特别是在医生等卫生保健人员的数量方面，是不够的。假设每位患者的医生数量是患者满意度的决定因素之一，分析了对新医生、专科医生和外国医生的最佳投资。采用最优控制理论确定新医生(新毕业生)、专科医生和外国医生的最优投资策略，以在固定的时间范围内最大化患者的净(成本)满意度。研究发现，当一国在规划初期总医生和专科医生数量不足时，应以时间的二次函数增加对新医生的投入，线性增加本地专科医生，同时聘请外国医生，使其成本与患者的边际满意度相等。

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来源期刊

Network Modeling and Analysis in Health Informatics and Bioinformatics MATHEMATICAL & COMPUTATIONAL BIOLOGY-

CiteScore

5.40

自引率

4.30%

发文量

期刊介绍： NetMAHIB publishes original research articles and reviews reporting how graph theory, statistics, linear algebra and machine learning techniques can be effectively used for modelling and analysis in health informatics and bioinformatics. It aims at creating a synergy between these disciplines by providing a forum for disseminating the latest developments and research findings; hence, results can be shared with readers across institutions, governments, researchers, students, and the industry. The journal emphasizes fundamental contributions on new methodologies, discoveries and techniques that have general applicability and which form the basis for network based modelling, knowledge discovery, knowledge sharing and decision support to the benefit of patients, healthcare professionals and society in traditional and advanced emerging settings, including eHealth and mHealth .