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.
Ключевые слова: medical treatment, health care, resources, economic efficiency, cognitive modeling
Список литературы:
Lane R., Russell G., Bardoel E.A. et al. When Colocation Is not Enough: A Case Study of General Practitioner Super Clinics in Australia. Australian Journal of Primary Health, 2017, vol. 23, iss. 2, pp. 107–113. URL: Link
Lawn S., Lloyd A., King A. et al. Integration of Primary Health Services: Being Put Together Does not Mean They will Work Together. BMC Research Notes, 2014, vol. 7, p. 66. URL: Link
Santosa A., Rocklöv J., Högberg U., Byass P. Achieving a 25% Reduction in Premature Non-Communicable Disease Mortality: The Swedish Population as a Cohort Study. BMC Medicine, 2015, vol. 13, p. 65. URL: Link
Song X., Quek R.G.W., Gandra S.R. et al. Productivity Loss and Indirect Costs Associated with Cardiovascular Events and Related Clinical Procedures. BMC Health Services Research, 2015, vol. 15, p. 245. URL: Link
Maru S., Byrnes J., Carrington M.J. et al. Economic Implications of Cardiovascular Disease Management Programs: Moving beyond One-Off Experiments. Expert Review of Pharmacoeconomics & Outcomes Research, 2015, vol. 15, iss. 4, pp. 657–666. URL: Link
Atehortúa S., Ceballos M., Gaviria C.F., Mejía A. Evaluación de la Calidad Metodológica de la Literatura en Evaluación Económica en Salud en Colombia: una Revisión Sistemática. Biomedica, 2013, vol. 33, no. 4, pp. 615–630. URL: Link
Ngalesoni F., Ruhago G., Norheim O.F., Robberstad B. Economic Cost of Primary Prevention of Cardiovascular Diseases in Tanzania. Health Policy and Planning, 2005, vol. 30, iss. 7, pp. 875–884. URL: Link
Dong G.N. Performing Well in Financial Management and Quality of Care: Evidence from Hospital Process Measures for Treatment of Cardiovascular Disease. BMC Health Services Research, 2015, vol. 15, no. 1, p. 45. URL: Link
De Gruyter E., Ford G., Stavreski B. Economic and Social Impact of Increasing Uptake of Cardiac Rehabilitation Services – A Cost Benefit Analysis. Heart, Lung and Circulation, 2016, vol. 25, iss. 2, pp. 175–183. URL: Link
Gilfillan R.J., Tomcavage J., Rosenthal M.B. et al. Value and the Medical Home: Effects of Transformed Primary Care. The American Journal of Managed Care, 2010, vol. 16, no. 8, pp. 607–614. URL: Link
Spann S.J. Task Force Report 6. Report on Financing the New Model of Family Medicine. Annals of Family Medicine, 2004, vol. 2, suppl. 3, pp. 1–21. URL: Link
Nahhas G.J., Daguise V., Ortaglia A., Merchant A.T. Determinants of Major Cardiovascular Risk Factors Among Participants of the South Carolina WISEWOMAN Program, 2009–2012. Preventing Chronic Disease, 2014, vol. 11. URL: Link
Hendriks M.E., Bolarinwa O.A., Nelissen H.E. et al. Costs of Cardiovascular Disease Prevention Care and Scenarios for Cost Saving: A Micro-Costing Study from Rural Nigeria. Journal of Hypertension, 2015, vol. 33, no. 2, pp. 376–384. URL: Link
Muka T., Imo D., Jaspers L. et al. The Global Impact of Non-Communicable Diseases on Healthcare Spending and National Income: A Systematic Review. European Journal of Epidemiology, 2015, vol. 30, iss. 4, pp. 251–277. URL: Link
Rutman L.E., Migita R., Woodward G.A., Klein E.J. Creating a Leaner Pediatric Emergency Department: How Rapid Design and Testing of a Front-End Model Led to Decreased Wait Time. Pediatric Emergency Care, 2015, vol. 31, no. 6, pp. 395–398. URL: Link
Joseph K.T., Rice K., Li C. Integrating Equity in a Public Health Funding Strategy. Journal of Public Health Management and Practice, 2016, vol. 22, suppl. 1, pp. 68–76. URL: Link
Elf M., Fröst P., Lindahl G., Wijk H. Shared Decision Making in Designing New Healthcare Environments – Time to Begin Improving Quality. BMC Health Services Research, 2015, vol. 15, no. 1, p. 114. URL: Link
Penno E., Gauld R., Audas R. How Are Population-Based Funding Formulae for Healthcare Composed? A Comparative Analysis of Seven Models. BMC Health Services Research, 2013, vol. 13, p. 470. URL: Link
Lantz P.M., Alexander J.A., Adolph C., Montgomery J.P. State Government Organization of Health Services, 1990–2009: Correlates and Consequences. Journal of Public Health Management and Practice, 2014, vol. 20, iss. 2, pp. 160–167. URL: Link
Hecht R., Bollinger L., Stover J. et al. Critical Choices in Financing the Response to the Global HIV/AIDS Pandemic. Health Affairs, 2009, vol. 28, no. 6, pp. 1591–1605. URL: Link
Yuen E.J., Louis D.Z., Di Loreto P., Gonnella J.S. Modeling Risk-Adjusted Capitation Rates for Umbria, Italy. The European Journal of Health Economics, 2003, vol. 4, iss. 4, pp. 304–312. URL: Link
Barlow J., Roehrich J., Wright S. Europe Sees Mixed Results from Public-Private Partnerships for Building and Managing Health Care Facilities and Services. Health Affairs, 2013, vol. 32, no. 1, pp. 146–154. URL: Link
Librero J., Ibañez B., Martínez-Lizaga N. et al. Applying Spatio-Temporal Models to Assess Variations Across Health Care Areas and Regions: Lessons from the Decentralized Spanish National Health System. PLOS ONE, 2017, vol. 12, no. 2. URL: Link
Cardoso T., Oliveira M.D., Barbosa-Póvoa A., Nickel S. Modeling the Demand for Long-Term Care Services under Uncertain Information. Health Care Management Science, 2012, vol. 15, iss. 4, pp. 385–412. URL: Link
Tufts J.B., Weathersby P.K., Rodriguez F.A. Modeling the Unites States Government's Economic Cost of Noise-Induced Hearing Loss for a Military Population. Scandinavian Journal of Work, Environment & Health, 2010, vol. 36, no. 3, pp. 242–249. URL: Link
De Soárez P.C., Soares M.O., Novaes H.M.D. Modelos de Decisão para Avaliações Econômicas de Tecnologias em Saúde. Ciência & Saúde Coletiva, 2014, vol. 19, no. 10, pp. 4209–4222. URL: Link
Andreeva O.V., Takmazyan A.S., Otrishko M.O. [Main trends in healthcare financing in the region in response to a reinforced fulfillment of insurance principles of healthcare arrangement]. Finansovye issledovaniya = Financial Research, 2016, no. 4, pp. 171–181. URL: Link (In Russ.)
Baranovskii G.V., Badyukov V.F. [Model of regional decision-making of health care funding under full and part uncertainty]. Perspektivy nauki = Science Prospects, 2013, no. 9, pp. 116–119. URL: Link.pdf (In Russ.)
Baranovsky G.V. [Regional model of financial and economy security of health care system]. Nauka i biznes: puti razvitiya = Science and Business: Development Ways, 2013, no. 9, pp. 99–102. URL: Link.pdf (In Russ.)
Guseva S.V., Ivanova N.G. [Programs budgeting in healthcare at the regional level]. Izvestiâ Sankt-Peterburgskogo gosudarstvennogo èkonomičeskogo universiteta, 2016, no. 1, pp. 32–41. URL: Link (In Russ.)
Murzaeva O.V. [Regional aspects of financing of the health care (on example of Republic of Mordovia)]. Biznes. Obrazovanie. Pravo = Business. Education. Law, 2012, no. 2, pp. 188–197. URL: Link (In Russ.)
Lobkova E.V., Petrichenko A.S. [Managing the effectiveness of the regional health system]. Regional'naya ekonomika: teoriya i praktika = Regional Economics: Theory and Practice, 2018, vol. 16, iss. 2, pp. 274–295. (In Russ.) URL: Link