OECD Ülkelerine ait Sağlık Ekonomilerinin Değerlendirilmesi: Çok Amaçlı İstatistiksel Optimizasyon Modeli
Year 2021,
Volume: 5 Issue: 1, 197 - 206, 29.06.2021
Abdulkadir Atalan
,
Cem Çağrı Dönmez
Abstract
Sağlık sistemleri, ülke ekonomilerini etkileyen en önemli faktörlerden birdir. Bu çalışmada, OECD üyelerinin sağlık harcamalarını (SH) ve kişi başına düşen sağlık harcamalarını (kbSH) değerlendirmek için Ekonomik İşbirliği ve Kalkınma Teşkilatı (OECD) ülkelerine ait sağlık sistemlerinin altyapısı ve ekonomik yapısı tartışılmıştır. İstatistiksel optimizasyon analizi ile OECD üyelerindeki sağlık sistemlerini etkileyen faktörlerin uygulanabilir değerlerini hesaplamak için sağlık ekonomisi ile ilgili faktörleri belirlenerek, bu faktörlerin önemlilik oranlarını analiz ettik. İstatistiksel analiz aracılığıyla çok amaçlı optimizasyon modeli (MOOM) kullanılarak elde edilen uygulanabilir değerler içerisinde OECD ülkelerinin SH’si minimize edilmiş ve % 29,13 oranında iyileşme sağlanmıştır. İkinci amaç fonksiyonu ise OECD üyeleri için kbSH’yi maksimize etmek amacıyla en az kbSH değeri 5.282,37 dolar olarak tahmin edilmiştir. Sonuç olarak sosyal sağlık sistemi olmayan ülkelerde SH miktarlarının aşırı olduğu algılanmaktadır. Bu durumun temel nedeni, sağlık sektörünün o ülkelerdeki bir işletme olarak algılanmaktadır.
References
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- Mason, K., Duggan, J., & Howley, E. (2017). Multi-objective dynamic economic emission dispatch using particle swarm optimisation variants. Neurocomputing, 270(Supplement C), 188–197. https://doi.org/https://doi.org/10.1016/j.neucom.2017.03.086
- McCoskey, S. K., & Selden, T. M. (1998). Health care expenditures and GDP: panel data unit root test results. Journal of Health Economics, 17(3), 369–376. https://doi.org/https://doi.org/10.1016/S0167-6296(97)00040-4
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Evaluation of Healthcare Economics of OECD Countries: Multi-Objective Statistical Optimization Model
Year 2021,
Volume: 5 Issue: 1, 197 - 206, 29.06.2021
Abdulkadir Atalan
,
Cem Çağrı Dönmez
Abstract
Healthcare systems comprise the most crucial factors affecting countries economically. In this study, the infrastructure and economic structure of healthcare systems belonging to the Organization for Economic Co-operation and Development (OECD) countries are discussed to evaluate the healthcare expenditures (HE) and healthcare expenditures per capita (pcHE) of OECD members. We have identified factors related to healthcare economics and analyzed the significance ratios of these factors to calculate the feasible values of the factors affecting the healthcare systems in the OECD members by statistical optimization analysis. Within the feasible values obtained by using a multi-objective optimization model (MOOM) because of statistical analysis, the HE of OECD countries was minimized, and an improvement of 29.13% was achieved. The second objective function aimed to maximize the pcHE that was estimated to be at least $5,282.37 for the OECD members. Consequently, in countries that do not have a social healthcare system, it is perceived that HE amounts are excessive. The fundamental reason for this situation represents the healthcare sector’s perception as a business in those countries
References
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- Albouy, V., Davezies, L., & Debrand, T. (2010). Health expenditure models: A comparison using panel data. Economic Modelling, 27(4), 791–803. https://doi.org/https://doi.org/10.1016/j.econmod.2010.02.006
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- Atalan, A. (2019). THE IMPACTS OF HEALTHCARE RESOURCES ON SERVICES OF EMERGENCY DEPARTMENT: DISCRETE EVENT SIMULATION WITH BOX-BEHNKEN DESIGN. PONTE International Scientific Researchs Journal, 75(6), 12–23. https://doi.org/10.21506/j.ponte.2019.6.10
- Atalan, A. (2020). Forecasting for Healthcare Expenditure of Turkey Covering the Years of 2018-2050. Gümüşhane Üniversitesi Sağlık Bilimleri Dergisi, 9(1), 8–16. https://doi.org/10.37989/gumussagbil.538111
- Atalan, A., Cinar, Z., & Cinar, M. (2020). A TRENDLINE ANALYSIS FOR HEALTHCARE EXPENDITURE PER CAPITA OF OECD MEMBERS. Sigma Journal Of Engineering And Natural Sciences, 10(3), 23–35.
- Atalan, A., & Donmez, C. (2019). Employment of Emergency Advanced Nurses of Turkey: A Discrete-Event Simulation Application. Processes, 7(1), 48. https://doi.org/10.3390/pr7010048
- Baltagi, B. H., & Moscone, F. (2010). Health care expenditure and income in the OECD reconsidered: Evidence from panel data. Economic Modelling, 27(4), 804–811. https://doi.org/https://doi.org/10.1016/j.econmod.2009.12.001
- Bichay, N. (2020). Health insurance as a state institution: The effect of single-payer insurance on expenditures in OECD countries. Social Science & Medicine, 113454. https://doi.org/10.1016/j.socscimed.2020.113454
- C., W. M., & B., S. W. (1977). Foundations of Cost-Effectiveness Analysis for Health and Medical Practices. New England Journal of Medicine, 296(13), 716–721. https://doi.org/10.1056/NEJM197703312961304
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- Deb, K., & Kalyanmoy, D. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons, Inc.
- Dukhanin, V., Searle, A., Zwerling, A., Dowdy, D. W., Taylor, H. A., & Merritt, M. W. (2018). Integrating social justice concerns into economic evaluation for healthcare and public health: A systematic review. Social Science and Medicine, 198, 27–35. https://doi.org/10.1016/j.socscimed.2017.12.012
- Gerdtham, U. G., Søgaard, J., Andersson, F., & Jönsson, B. (1992). An econometric analysis of health care expenditure: A cross-section study of the OECD countries. Journal of Health Economics, 11(1), 63–84. https://doi.org/https://doi.org/10.1016/0167-6296(92)90025-V
- Gregori, D., Petrinco, M., Bo, S., Desideri, A., Merletti, F., & Pagano, E. (2011). Regression models for analyzing costs and their determinants in health care: an introductory review. International Journal for Quality in Health Care, 23(3), 331–341. https://doi.org/10.1093/intqhc/mzr010
- Iii, J. H. E., Hwang, Y., & Nagarajan, N. J. (2001). Management control and hospital cost reduction: additional evidence. Journal of Accounting and Public Polic, 20(1), 73–88.
- Jones, A. M., Lomas, J., & Rice, N. (2015). Healthcare Cost Regressions: Going Beyond the Mean to Estimate the Full Distribution. Health Economics, 24(9), 1192–1212. https://doi.org/10.1002/hec.3178
- Liu, Y., Lei, H., Zhang, D., & Wu, Z. (2018). Robust optimization for relief logistics planning under uncertainties in demand and transportation time. Applied Mathematical Modelling, 55(Supplement C), 262–280. https://doi.org/https://doi.org/10.1016/j.apm.2017.10.041
- Malehi, A. S., Pourmotahari, F., & Angali, K. A. (2015). Statistical models for the analysis of skewed healthcare cost data: a simulation study. Health Economics Review, 5, 11. https://doi.org/10.1186/s13561-015-0045-7
- Mason, K., Duggan, J., & Howley, E. (2017). Multi-objective dynamic economic emission dispatch using particle swarm optimisation variants. Neurocomputing, 270(Supplement C), 188–197. https://doi.org/https://doi.org/10.1016/j.neucom.2017.03.086
- McCoskey, S. K., & Selden, T. M. (1998). Health care expenditures and GDP: panel data unit root test results. Journal of Health Economics, 17(3), 369–376. https://doi.org/https://doi.org/10.1016/S0167-6296(97)00040-4
- Mihaylova, B., Briggs, A., O’Hagan, A., & Thompson, S. G. (2011). Review of Statistical Methods for Analysing Healthcare Resources and Costs. Health Economics, 20(8), 897–916. https://doi.org/10.1002/hec.1653
- Muyl, F., Dumas, L., & Herbert, V. (2004). Hybrid method for aerodynamic shape optimization in automotive industry. Computers and Fluids, 33(5), 849–858. https://doi.org/https://doi.org/10.1016/j.compfluid.2003.06.007
- Ngatchou, P., Zarei, A., & El-Sharkawi, A. (2005). Pareto Multi Objective Optimization. Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems, 84–91. https://doi.org/10.1109/ISAP.2005.1599245
- OECD. (2016a). OECD Data Health Expenditure (Percent of GDP). https://doi.org/http://stats.oecd.org/Index.aspx?DataSetCode=SHA
- OECD. (2016b). OECD Data Health Expenditure Per Capita. https://doi.org/https://data.oecd.org/healthres/health-spending.htm
- OECD. (2017a). Life expectancy at birth 2015. https://doi.org/https://data.oecd.org/healthstat/life-expectancy-at-birth.htm
- OECD. (2017b). OECD Data Health Care Resources 2015. https://doi.org/http://stats.oecd.org/Index.aspx?DataSetCode=HEALTH_REAC
- OECD. (2017c). Pharmaceutical spending Total, % of health spending, 2015. https://doi.org/https://data.oecd.org/healthres/pharmaceutical-spending.htm
- OECD. (2017d). The Organisation for Economic Co-operation and Development: Members and partners. http://www.oecd.org/about/membersandpartners/#d. en.194378
- OECD. (2017e). World Health Organization’s Global Health Workforce Statistics, OECD, supplemented by country data. Physicians (per 1,000 people). https://data.worldbank.org/indicator/SH.MED.PHYS.ZS
- Palasca, S., & Jaba, E. (2015). Economic Crisis’ Repercussions on European Healthcare Systems. Procedia Economics and Finance, 23(Supplement C), 525–533. https://doi.org/https://doi.org/10.1016/S2212-5671(15)00568-7
- Steiner, M. T. A., Datta, D., Neto, P. J. S., Scarpin, C. T., & Figueira, J. R. (2015). Multi-objective optimization in partitioning the healthcare system of Parana State in Brazil. Omega, 52(Supplement C), 53–64. https://doi.org/https://doi.org/10.1016/j.omega.2014.10.005
- WBG. (2017). The World Bank, GDP Per Capita, (current international $) 2016. https://doi.org/https://data.worldbank.org/indicator/NY.GDP.PCAP. PP.CD