THE EFFECT OF BED CAPACITY AND PUBLIC HEALTH EXPENDITURES ON PATIENT SATISFACTION LEVEL: THE CASE OF DEVELOPED AND DEVELOPING COUNTRIES
Yıl 2024,
Sayı: 65, 269 - 284, 21.11.2024
Seval Selvi Sarıgül
,
Murat Konca
,
İsmail Biçer
Öz
The aim of this study was to reveal the effect of the number of beds and the share of public health expenditures in gross domestic product on patient satisfaction, affecting the technical efficiency scores of health systems in developed and developing countries, and to compare the efficiency levels across countries by using the stochastic frontier analysis method. Another aim of the study was to determine whether the financing model of the study countries had an impact on the technical efficiency scores. In this context, the input variables of the study were determined as the number of beds per 1.000 people and the share of public health expenditures in gross domestic product, while the output variable was determined as the satisfaction with healthcare services. The study included 38 countries with available data for 2019. As a result of the analyses, it was determined that the number of beds per 1,000 people increased satisfaction with healthcare services, but this increase was not found to be statistically significant. However, it was determined that the share of public health expenditures in gross domestic product increased the satisfaction with healthcare services in a statistically significant way. Accordingly, a 1% increase in the share of public health expenditures in gross domestic product increased satisfaction with healthcare services by 0.237%. In addition, Luxembourg, the Netherlands and Norway had the highest technical efficiency scores, while Chile, Romania and Brazil had the lowest. Finally, it was found that the financing model did not significantly affect the technical efficiency scores.
Kaynakça
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- Ahangar, A., Ahmadi, A. M., Mozayani, A. H., Dizaji, S. F., ve Safarani, S. (2019). “Transition of health financing, cost risk-sharing and risk-pooling models in the health sector: A systematic review (1990 - 2019)”, Iran Red Crescent Med J., 21/12, e63215.
- Aigner, D., Lovell, C. K. ve Schmidt, P. (1977). “Formulation and estimation of stochastic frontier production function models”, Journal of Econometrics, 6/1, 21-37.
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- Asandului, L., Roman, M. ve Fatulescu, P. (2014). “The efficiency of healthcare systems in Europe: A data envelopment analysis approach”, Procedia Economics and Finance, 10, 261-268.
- Başol, E. (2015). “Gelişmekte olan ülkelerde strateji: Sağlık sisteminde sevk zinciri”, Balkan Sosyal Bilimler Dergisi, 4/8, 128-140.
- Benneyan, J. C., Sunnetci, A. ve Ceyhan, M. E. (2008). “Data envelopment analysis models for ıdentifying and benchmarking the best healthcare processes”, International Journal of Six Sigma and Competitive Advantage, 4/3, 305-331.
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- Chen, Z., Chen, X., Gan, X., Bai, K., Baležentis, T. C. ve Cui, L. (2020). “Technical efficiency of regional public hospitals in China based on the three-stage DEA”. Int. J. Environ. Res. Public Health, 17, 1-17. https://doi.org/10.3390/ijerph17249383
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YATAK KAPASİTESİNİN VE KAMU SAĞLIK HARCAMALARININ HASTA MEMNUNİYET DÜZEYİ ÜZERİNDEKİ ETKİSİ: GELİŞMİŞ VE GELİŞMEKTE OLAN ÜLKELER ÖRNEĞİ
Yıl 2024,
Sayı: 65, 269 - 284, 21.11.2024
Seval Selvi Sarıgül
,
Murat Konca
,
İsmail Biçer
Öz
Bu çalışmanın amacı stokastik sınır analizi yöntemi ile gelişmiş ve gelişmekte olan ülkelerin sağlık sistemlerinin teknik etkinlik skorlarını etkileyen yatak sayısının ve kamu sağlık harcamalarının gayrisafi yurt içi hâsıla içindeki payının hasta memnuniyeti üzerindeki etkisini ortaya koymak ve ülkeler arasındaki etkinlik düzeylerini karşılaştırmaktır. Ülkelerin finansman modellerinin teknik etkinlik skorları üzerinde etkisinin olup olmadığını belirlemek, çalışmanın bir diğer amacıdır. Bu kapsamda çalışmanın girdi değişkenleri 1.000 kişiye düşen yatak sayısı ve kamu sağlık harcamalarının gayrisafi yurtiçi hâsıla içindeki payı, çıktı değişkeni ise sağlık hizmetlerinden memnuniyet oranı olarak belirlenmiştir. Çalışmaya 2019 yılı verisine ulaşılabilen 38 ülke dâhil edilmiştir. Analizler sonucunda 1.000 kişiye düşen yatak sayısının, sağlık hizmetlerinden memnuniyet oranını artırdığı, fakat söz konusu artışın istatistiksel olarak anlamlı olmadığı tespit edilmiştir. Ancak kamu sağlık harcamalarının gayrisafi yurtiçi hâsıla içindeki payının, sağlık hizmetlerinden memnuniyet oranını istatistiksel olarak anlamlı şekilde artırdığı belirlenmiştir. Buna göre, kamu sağlık harcamalarının gayrisafi yurtiçi hâsıla içindeki payında meydana gelecek %1’lik bir artış, sağlık hizmetlerinden memnuniyet oranını %0,237 artıracaktır. Ayrıca en yüksek teknik etkinlik skoruna Lüksemburg, Hollanda ve Norveç sahip olurken, Şili, Romanya ve Brezilya en düşük etkinlik skoruna sahip ülkeler olmuştur. Son olarak, kullanılan finansman modelinin teknik etkinlik skorlarını anlamlı şekilde etkilemediği saptanmıştır.
Etik Beyan
“Yatak Kapasitesinin ve Kamu Sağlık Harcamalarının Hasta Memnuniyet Düzeyi Üzerindeki Etkisi: Gelişmiş ve Gelişmekte Olan Ülkeler Örneği” isimli bu çalışmada ikincil veri seti kullanıldığından etik kurul izni gerektirmemektedir.
Destekleyen Kurum
“Yatak Kapasitesinin ve Kamu Sağlık Harcamalarının Hasta Memnuniyet Düzeyi Üzerindeki Etkisi: Gelişmiş ve Gelişmekte Olan Ülkeler Örneği” isimli bu çalışmayı destekleyen herhangi bir kurum ya da kuruluş bulunmamaktadır.
Kaynakça
- Afonso, A. Ve Aubyn, M. S. (2005). “Non-parametric approaches to education and health efficiency in OECD countries”, Journal of Applied Economics, 8/2, 227-246.
- Ahangar, A., Ahmadi, A. M., Mozayani, A. H., Dizaji, S. F., ve Safarani, S. (2019). “Transition of health financing, cost risk-sharing and risk-pooling models in the health sector: A systematic review (1990 - 2019)”, Iran Red Crescent Med J., 21/12, e63215.
- Aigner, D., Lovell, C. K. ve Schmidt, P. (1977). “Formulation and estimation of stochastic frontier production function models”, Journal of Econometrics, 6/1, 21-37.
- Al-Refaie, A. (2013). “A structural model to investigate factors affect patient satisfaction and revisit intention in Jordanian hospitals”, In Investigations into Living Systems, Artificial Life, and Real-World Solutions, 136-147.
- Arhin, K., Oteng-Abayie, E. F., ve Novignon, J. (2023). “Effects of healthcare financing policy tools on health system efficiency: Evidence from sub-Saharan Africa”. Heliyon, 9/10, 1-14.
- Asandului, L., Roman, M. ve Fatulescu, P. (2014). “The efficiency of healthcare systems in Europe: A data envelopment analysis approach”, Procedia Economics and Finance, 10, 261-268.
- Başol, E. (2015). “Gelişmekte olan ülkelerde strateji: Sağlık sisteminde sevk zinciri”, Balkan Sosyal Bilimler Dergisi, 4/8, 128-140.
- Benneyan, J. C., Sunnetci, A. ve Ceyhan, M. E. (2008). “Data envelopment analysis models for ıdentifying and benchmarking the best healthcare processes”, International Journal of Six Sigma and Competitive Advantage, 4/3, 305-331.
- Chai, P., Zhang, Y., Zhou, M., Liu, S. ve Kinfu, Y. (2019). “Technical and scale efficiency of provincial health systems in China: A bootstrapping data envelopment analysis”, BMJ Open, 9/8, 1-9.
- Chen, Z., Chen, X., Gan, X., Bai, K., Baležentis, T. C. ve Cui, L. (2020). “Technical efficiency of regional public hospitals in China based on the three-stage DEA”. Int. J. Environ. Res. Public Health, 17, 1-17. https://doi.org/10.3390/ijerph17249383
- Clayton, A. C. (2010). “Assessing the productive efficiency of US health care: Comparison of analytical methods”, Honors Projects, 106. Retrieved http://digitalcommons.iwu.edu/econ_honproj/106/ (Erişim Tarihi: 21.02.2024).
- Coelli, T. (1995). “Estimators and hypothesis tests for a stochastic frontier function: A Monte Carlo analysis”, Journal of Productivity Analysis, 6, 247-268.
- Collins, C. ve Green, A. (1994). “Decentralization and primary health care: Some negative ımplications in developing countries”, International Journal of Health Services, 24/3, 459-475.
- Cylus, J., Papanicolas, I. ve Smith, P. (2016). “A Framework for Thinking About Health System Efficiency, in Cylus”, Health System Efficiency: How to Make Measurement Matter for Policy and Management, (Ed: Papanicolas ve Smith), World Health Organization, United Kingdom, pp. 1-20.
- Çağlar, A. ve Gülel, F. E. (2015). “Sağlık hizmetlerinden memnuniyet: Etkinlik ve mekansal etkileşim analizi”, Journal of Life Economics, 2/2, 29-58.
- de Cos, P. H. ve Moral-Benito, E. (2014). “Determinants of health-system efficiency: Evidence from OECD countries”, International Journal of Health Care Finance and Economics, 14, 69-93.
- Demirci, Ş., Konca, M., ve İlgün, G. (2020). “Sağlık finansmanının sağlık sistemleri performansına etkisi: Avrupa Birliği üyesi ve adayı ülkeler üzerinden bir değerlendirme”, Sosyoekonomi, 28/43, 229-242.
- Dhaoui, I. (2019). “Healthcare system efficiency and ıts determinants: A two-stage data envelopment analysis (DEA) from MENA Countries”, Economic Research Forum (ERF), Giza, Egypt.
- Erden, B., ve Yanık, R. (2022). “Türkiye’de sağlık harcamaları ve 2020 yılı verilerine göre sağlık sistemi en gelişmiş 10 ülke ile Türkiye’nin karşılaştırılması. Para ve sermaye piyasası araştırmaları”. Orion Akademi.
- Evans, D. B., Tandon, A., Murray, C. J. ve Lauer, J. A. (2001). “Comparative efficiency of national health systems: Cross national econometric analysis”, BMJ, 323/7308, 307-310.
- Fang, H., Eggleston, K., Hanson, K. ve Wu, M. (2019). “Enhancing financial protection under China’s social health insurance to achieve universal health coverage”, BMJ, 36, 1-4.
- Farrell, M. (1957). “The measurement of productive efficiency”, Journal of the Royal Statistical Society, Series A (Statistics in Society), 120, 253-290.
- FasterCapital, (2024). Maximum likelihood estimation: estimating excellence: The impact of maximum likelihood in SFA, https://www.fastercapital.com/content/Maximum-Likelihood-Estimation--Estimating-Excellence--The-Impact-of-Maximum-Likelihood-in-SFA.html#MLE-vsOther-Estimation-Techniques (Erişim Tarihi: 15.10.2024).
- Feng, C., Wang, H., Lu, N., Chen, T., He, H., Lu, Y., ve Tu, X. M. (2014). “Log-transformation and its implications for data analysis”, Shanghai Archives of Psychiatry, 26/2, 105-109.
- Grosskopf, S., Self, S. ve Zaim, O. (2006). “Estimating the efficiency of the system of healthcare financing in achieving better health”, Applied Economics, 38/13, 1477-1488.
- Hadad, S., Hadad, Y. ve Simon-Tuval, T. (2013). “Determinants of healthcare system’s efficiency in OECD countries”, The European Journal of Health Economics, 14, 253-265.
- Hamidi, S. ve Akinci, F. (2016). “Measuring efficiency of health systems of the Middle East and North Africa (MENA) region using stochastic frontier analysis”, Applied Health Economics and Health Policy, 14, 337-347.
- Hu, L., Ding, H., Liu, S., Wang, Z., Hu, G., ve Liu, Y. (2020). “Influence of patient and hospital characteristics on inpatient satisfaction in China's tertiary hospitals: A cross‐sectional study”. Health Expectations, 23/1, 115-124.
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