Agent-based modeling of regional healthcare: addressing the task of formalizing residents' medical activity

Agent-based modeling of regional healthcare: addressing the task of formalizing residents' medical activity

Автор: Dianov Sergei V., Kalashnikov Konstantin N., Rigin Vasilii A.

Журнал: Economic and Social Changes: Facts, Trends, Forecast @volnc-esc-en

Рубрика: Theoretical and methodological issues

Статья в выпуске: 1 т.15, 2022 года.

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The article addresses the task concerning the development of techniques for formalizing the behavior of agents-users of medical services in agent-based models designed to support decision-making on the spatial layout of health infrastructure facilities in the region. We analyze approaches to determining the behavior patterns of consumers of medical services and, on this basis, develop the structure of agents' behavior model. We consider the implementation of the proposed model with the help of fuzzy neural networks. While forming the network, we use the results of a sociological survey conducted by Vologda Research Center in the territory of the Vologda Oblast in 2020. Practical implementation of the network is carried out in the Microsoft Access environment. Using this tool, we conduct a number of experiments to determine residents' medical activity based on the initial data of the sociological survey. We use general scientific methods of formalization, abstraction, generalization, methods of system analysis, mathematical statistics, and fuzzy logic. The results of our work consist in designing the structure of behavior model for agents-consumers of medical services and methods for its implementation. Scientific novelty of our findings consists in the proposed structure of behavior model of agents-consumers of medical services and its practical implementation with the use of fuzzy neural networks in relation to the manifestation of medical activity. Practical significance of the results lies in the fact that the instrumental approaches proposed and partially tested in it will allow us to develop agent-based models of regional healthcare adequate to objective environmental conditions, taking into account citizens' attitudes and behavior motives in interaction with medical services. In the future, this will help us to put forward and adjust measures to improve the efficiency of spatial layout and functioning of networks. Further work will be related to the improvement of the proposed methods in the following areas: determining ways to train the developed fuzzy neural network and finding ways to implement the remaining elements of the developed model for agent behavior.

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Healthcare infrastructure facilities, medical services, medical activity, agent-based modeling, fuzzy neural networks

Короткий адрес: https://sciup.org/147237317

IDR: 147237317

Список литературы Agent-based modeling of regional healthcare: addressing the task of formalizing residents' medical activity

  • Andersen R.M. (1968). Behavioral Model of Families: Use of Health Services. Chicago: Center for Health Administration Studies, University of Chicago.
  • Badham J., Chattoe-Brown E., Gilbert N., Chalabi Z., Kee F., Hunter R. F. (2018). Developing agent-based models of complex health behaviour. Health Place. 54, 170-177. DOI: 10.1016/j.healthplace.2018.08.022
  • Bakhtizin A.R. (2008). Agent-orientirovannye modeli ekonomiki [Agent-Based Models of Economy]. Moscow: Ekonomika.
  • Dawid H., Neugart M. (2011). Agent-based Models for Economic Policy Design. Eastern Economic Journal, no. 37, 44–50.
  • Dianov S.V. (2020). The problem of optimal spatial placement of services for systems with mobile users. In: Materialy odinnadtsatoi zaochnoi mezhdunarodnoi nauchno-tekhnicheskoi konferentsii “Intellektual'no-informatsionnye tekhnologii i intellektual'nyi biznes (INFOS-2020)” (29–30 iyunya 2020 g.) [Proceedings of the Eleventh Virtual International Scientific and Technological Conference “Intellectual and Information Technologies and Intellectual Business (INFOS-2020)” (June 29–30, 2020)]. Vologda: VoGU. Pp. 53–55 (in Russian).
  • Dianov S.V., Shvetsov A.N. (2018). Ispol'zovanie nechetkikh neironnykh setei dlya poiska vozmozhnykh stsenariev povedeniya v mul'tiagentnykh sistemakh organizatsionnogo upravleniya. In: Vuzovskaya nauka – regionam. Materialy XVI Vserossiiskoi nauchnoi konferentsii s mezhdunarodnym uchastiem. Vologda. Pp. 77–79 (in Russian).
  • Gaffard J.-L., Napoletano M. (2012). Agent-based Models and Economic. Paris: OFCE. 448 p.
  • Gupta M.M. (1994). Fuzzy neural networks: theory and applications, Proc. SPIE 2353, Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision. Available at https://doi.org/10.1117/12.188903
  • Katz B.P., Freund D.A., Heck D.A., Dittus R.S., Paul J.E., Wright J., Coyte P., Holleman E., Hawker G. (1996). Demographic variation in the rate of knee replacement: a multi-year analysis. Health Services Research, 31(2), 125–140.
  • Lurie N., Slater J., McGovern P., Ekstrum J., Quam L., Margolis K. (1993). Preventive care for women. Does the sex of the physician matter? N Engl J Med., 12, 329(7), 478–482. DOI: 10.1056/NEJM199308123290707
  • Makarov V.L., Bakhtizin A.R., Sushko E.D. (2016). Agent-based models as a means of testing of management solutions. Upravlencheskoe konsul'tirovanie=Administrative Consulting, 12, 16–25 (in Russian).
  • Makarov V.L., Bakhtizin A.R., Sushko E.D., Sushko G.B. (2019). Agent-based supercomputer demographic model of Russia: approbation analysis. Ekonomicheskie i sotsial'nye peremeny: fakty, tendentsii, prognoz=Economic and Social Changes: Facts, Trends, Forecast, 12(6), 74–90. DOI: 10.15838/esc.2019.6.66.4 (in Russian).
  • Mendritzki S. (2010). Artificial Policy: Examining the Use of Agent-Based Modeling in Policy Contexts. M.S. Thesis. Alberta: University of Calgary. 130 p.
  • Mikhailova Yu.V., Leonov S.A., Son I.M. et al. (2007). Current state and directions of development of national medical statistics. Sotsial'nye aspekty zdorov'ya naseleniya=Social Aspects of Population Health, 1(1). Available at: http://vestnik.mednet.ru/content/view/21/30 (accessed: November 10, 2021; in Russian).
  • Mirowsky J., Ross C.E. (1983). Patient satisfaction and visiting the doctor: A self-regulating system. Social Science & Medicine, 17(18), 1353–1361. Available at https://doi.org/10.1016/0277-9536(83)90195-8
  • Nichol M.B., Stimmel G.L., Lange S.C. (1995). Factors predicting the use of multiple psychotropic medications. The Journal of Clinical Psychiatry, 56(2), 1–66.
  • Pokrovskaya S.E. (2012). Factors forming medical aid appealability. Sotsial'nye aspekty zdorov'ya naseleniya=Social Aspects of Population Health, 25(3), 2 (in Russian).
  • Pottick K., Hansell S., Gutterman E., White H.R. (1995). Factors associated with inpatient and outpatient treatment for children and adolescents with serious mental illness. Journal of the American Academy of Child & Adolescent Psychiatry, 34(4), 425–433. Available at https://doi.org/10.1097/00004583-199504000-00009
  • Rusinova N.L., Panova L.V. (2002). Access to health services: Methodological approaches and measurement methods. Zhurnal sotsiologii i sotsial'noi antropologii=Journal of Sociology and Social Anthropology, 5(4), 147–163 (in Russian).
  • Shvetsov A.N., Dianov S.V. (2018). Using fuzzy neural networks to determine reactive behavior in multi-agent organizational management systems. Vestnik Vologodskogo gosudarstvennogo universiteta. Seriya: Tekhnicheskie nauki=Bulletin of Vologda State University. Series: Technical Sciences, 1(1), 64–69 (in Russian).
  • Silverman B.G. (2014). Systems approach to healthcare: Agent-based modeling, community mental health, and population well-being. Artificial Intelligence in Medicine, 63(2). DOI: 10.1016/j.artmed.2014.08.006
  • Tracy M., Cerdá M., Keyes K.M. (2018). Agent-based modeling in public health: Current applications and future directions. Annual Review of Public Health, 39, 77–94. Available at: https://doi.org/10.1146/annurev-publhealth-040617-014317
  • Wennberg J.E., Barnes B.A., Zubkoff M. (1982). Professional uncertainty and the problem of supplier-induced demand. Social Science & Medicine, 16(7), 811–824.
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