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ИД «Финансы и кредит»






Digest Finance

The Financing Model of the Regional Health System

Vol. 23, Iss. 4, DECEMBER 2018

Received: 10 April 2018

Received in revised form: 6 June 2018

Accepted: 11 July 2018

Available online: 24 December 2018


JEL Classification: H51, I15, R13

Pages: 384–394


Kulikova O.M. Novosibirsk Research Hygiene Institute of the Russian Federal Service for Surveillance on Consumer Rights Protection and Human Wellbeing, Novosibirsk, Russian Federation


Usacheva E.V. Therapeutics Department, Municipal Outpatients' Clinic № 4, Omsk, Russian Federation


Shamis V.A. Siberian State Automobile and Highway University (SibADI), Omsk, Russian Federation


Nelidova A.V. Omsk State Medical University of the Ministry of Healthcare of the Russian Federation (OmSMU MOH Russia), Omsk, Russian Federation


Boush G.D. Omsk F.M. Dostoevsky State University, Omsk, Russian Federation


Subject The research devises the healthcare spending model in line with types and scope of medical aid, assesses indicators of the current and future planned periods.
Objectives The research is an attempt to optimize healthcare spending by improving the way it is earmarked in line with the region’s demand for certain types of medical aid and reallocating financial resources.
Methods We use the conceptual modeling and Python 3.
Results We devised the model to optimize expenditures in order to increment resources available for health care purposes by reallocating them in accordance with the analysis of the financial situation, classes of patients. Our model builds on the type of total medical expenditures on patients with certain diseases and adjustment of healthcare spending against the current year’s plans.
Conclusions and Relevance Expenditures could be optimized through their reallocation in line with the type of total spending, financial effectiveness class and adequacy of their planning for promising and effective medical interventions.

Keywords: medical treatment, health care, resources, economic efficiency, cognitive modeling


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