Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2020, , 1094 - 1104, 01.10.2020
https://doi.org/10.16984/saufenbilder.714736

Öz

Destekleyen Kurum

Ondokuz Mayıs Üniversitesi

Proje Numarası

PYO. SCIENCE. 1904.17.004

Kaynakça

  • A. Afonso and M. St Aubyn, “Non-parametric approaches to education and health efficiency in OECD countries,” Journal of Applied Economics, vol. 8, no. 2, pp. 227, 2005.
  • J. Spinks and B. Hollingsworth, “Health production and the socioeconomic determinants of health in OECD countries: the use of efficiency models,” Centre for Health Economics Working Paper 151, pp. 3, 2005.
  • A. Afonso and M. St Aubyn, “Relative efficiency of health provision: A DEA approach with non-discretionary inputs,” ISEG-UTL Economics Working Paper, no. 33, pp. 3, 2006.
  • J. Kujawska, “Measurement of healthcare system efficiency in OECD Countries,” Metody Ilościowe w Badaniach Ekonomicznych, vol. 16, no. 2, pp. 23-32, 2015.
  • V. R. Çetin and S. Bahçe, “Measuring the efficiency of health systems of OECD countries by data envelopment analysis,” Applied Economics, vol. 48, no. 37, pp. 3497-3507, 2016.
  • Y. A. Özcan and J. Khushalani, “Assessing the efficiency of public health and medical care provision in OECD countries after a decade of reform,” Central European Journal of Operations Research, vol. 25, no. 2, pp. 325-343, 2017.
  • D. Wranik, “Healthcare policy tools as determinants of health system efficiency: evidence from the OECD,” Health Economics, Policy, and Law, vol. 7, no. 2, pp. 197–226, 2012.
  • P. H. De Cos and E. Moral-Benito, “Determinants of health-system efficiency: evidence from OECD countries,” International Journal of Health Care Finance and Economics, vol. 14, no. 1, pp. 69-93, 2014.
  • T. Şenel and M. A. Cengiz, “A Bayesian approach for evaluation of determinants of health system efficiency using stochastic frontier analysis and beta regression,” Computational and Mathematical Methods in Medicine, vol. 2016, pp. 1-5, 2016.
  • V. Paris, M. Devaux, and L. Wei, “Health systems institutional characteristics: a survey of 29 OECD countries,” OECD Health Working Papers, no. 50, pp. 22-28, 2010.
  • D. Aigner, C. Lowell, and P. Schmidt, “Formulation and estimation of stochastic frontier production function models,” Journal of Econometrics, vol. 6, no. 1, pp. 21–37, 1977.
  • G. H. Dunteman, and M. H. R. Ho. “An introduction to generalized linear models”, vol. 145, Sage Publications, 2005.
  • D. Karaboğa, Artificial Intelligence Optimization Algorithms, Ankara: Nobel, 2011.
  • D. Karaboğa and B. Baştürk, “On the performance of artificial bee colony (ABC) algorithm,” Applied Soft Computing, vol. 8, no. 1, pp. 687-697, 2008.
  • J. H. Holland, Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence, USA: MIT Press, 1992.
  • Ç. Elmas, Artificial Intelligence Applications, Ankara: Seçkin, 2010.
  • R. Storn and K. Price, “Differential evolution a simple and efficient heuristic for global optimization over continuous spaces,” Journal of Global Optimization, vol. 11, no. 4, pp. 341-359, 1997.
  • T. Keskintürk, “Differential evolution Algorithm,” Istanbul Commerce University Journal of Science, vol. 9, pp. 85-99, 2006.
  • H. Akaike, “Information theory and extension of the maximum likelihood principle,” 2nd International Symposium on Information Theory, pp. 267-281, 1973.
  • Hurvich, C. M. and C. L. Tsai, “Regression and time series model selection in small samples,” Biometrika, vol. 76, no. 2, pp. 297-307, 1989.
  • G. Schwarz, “Estimating the dimension of model,” Annals of Statistics, vol. 6, pp. 461-464, 1978.
  • H. Bozdogan, “Model selection and Akaike’s Information Criterion (AIC): the general theory and its analytical extensions,” Psychometrika, vol. 52, no. 3, pp. 345-370, 1987.

Determining the Factors that Influence the Effectiveness of the Health Sector in the OECD Countries

Yıl 2020, , 1094 - 1104, 01.10.2020
https://doi.org/10.16984/saufenbilder.714736

Öz

The purpose of this study is to determine the factors that influence the effectiveness of the health sector by combining Stochastic Frontier Analysis (SFA), Generalized Linear Models (GLM) and Heuristic Algorithms methods. In accordance with this purpose, firstly, the health system efficiencies of 29 OECD countries are estimated by the SFA method. Within the scope of this study, it is also aimed to select the factors influencing the efficiency of the health systems in OECD countries by employing Heuristic Algorithm methods such as Artificial Bee Colony Algorithm, Genetic Algorithm, and Differential Evolution Algorithm. Furthermore, GLM’s such as Truncated, Normal, Gamma and Tweedie distributions are employed for comparisons.

Proje Numarası

PYO. SCIENCE. 1904.17.004

Kaynakça

  • A. Afonso and M. St Aubyn, “Non-parametric approaches to education and health efficiency in OECD countries,” Journal of Applied Economics, vol. 8, no. 2, pp. 227, 2005.
  • J. Spinks and B. Hollingsworth, “Health production and the socioeconomic determinants of health in OECD countries: the use of efficiency models,” Centre for Health Economics Working Paper 151, pp. 3, 2005.
  • A. Afonso and M. St Aubyn, “Relative efficiency of health provision: A DEA approach with non-discretionary inputs,” ISEG-UTL Economics Working Paper, no. 33, pp. 3, 2006.
  • J. Kujawska, “Measurement of healthcare system efficiency in OECD Countries,” Metody Ilościowe w Badaniach Ekonomicznych, vol. 16, no. 2, pp. 23-32, 2015.
  • V. R. Çetin and S. Bahçe, “Measuring the efficiency of health systems of OECD countries by data envelopment analysis,” Applied Economics, vol. 48, no. 37, pp. 3497-3507, 2016.
  • Y. A. Özcan and J. Khushalani, “Assessing the efficiency of public health and medical care provision in OECD countries after a decade of reform,” Central European Journal of Operations Research, vol. 25, no. 2, pp. 325-343, 2017.
  • D. Wranik, “Healthcare policy tools as determinants of health system efficiency: evidence from the OECD,” Health Economics, Policy, and Law, vol. 7, no. 2, pp. 197–226, 2012.
  • P. H. De Cos and E. Moral-Benito, “Determinants of health-system efficiency: evidence from OECD countries,” International Journal of Health Care Finance and Economics, vol. 14, no. 1, pp. 69-93, 2014.
  • T. Şenel and M. A. Cengiz, “A Bayesian approach for evaluation of determinants of health system efficiency using stochastic frontier analysis and beta regression,” Computational and Mathematical Methods in Medicine, vol. 2016, pp. 1-5, 2016.
  • V. Paris, M. Devaux, and L. Wei, “Health systems institutional characteristics: a survey of 29 OECD countries,” OECD Health Working Papers, no. 50, pp. 22-28, 2010.
  • D. Aigner, C. Lowell, and P. Schmidt, “Formulation and estimation of stochastic frontier production function models,” Journal of Econometrics, vol. 6, no. 1, pp. 21–37, 1977.
  • G. H. Dunteman, and M. H. R. Ho. “An introduction to generalized linear models”, vol. 145, Sage Publications, 2005.
  • D. Karaboğa, Artificial Intelligence Optimization Algorithms, Ankara: Nobel, 2011.
  • D. Karaboğa and B. Baştürk, “On the performance of artificial bee colony (ABC) algorithm,” Applied Soft Computing, vol. 8, no. 1, pp. 687-697, 2008.
  • J. H. Holland, Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence, USA: MIT Press, 1992.
  • Ç. Elmas, Artificial Intelligence Applications, Ankara: Seçkin, 2010.
  • R. Storn and K. Price, “Differential evolution a simple and efficient heuristic for global optimization over continuous spaces,” Journal of Global Optimization, vol. 11, no. 4, pp. 341-359, 1997.
  • T. Keskintürk, “Differential evolution Algorithm,” Istanbul Commerce University Journal of Science, vol. 9, pp. 85-99, 2006.
  • H. Akaike, “Information theory and extension of the maximum likelihood principle,” 2nd International Symposium on Information Theory, pp. 267-281, 1973.
  • Hurvich, C. M. and C. L. Tsai, “Regression and time series model selection in small samples,” Biometrika, vol. 76, no. 2, pp. 297-307, 1989.
  • G. Schwarz, “Estimating the dimension of model,” Annals of Statistics, vol. 6, pp. 461-464, 1978.
  • H. Bozdogan, “Model selection and Akaike’s Information Criterion (AIC): the general theory and its analytical extensions,” Psychometrika, vol. 52, no. 3, pp. 345-370, 1987.
Toplam 22 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka, Bilgisayar Yazılımı, Yazılım Testi, Doğrulama ve Validasyon, Yazılım Mühendisliği (Diğer), Matematik, Endüstri Mühendisliği
Bölüm Araştırma Makalesi
Yazarlar

Selin Ceren Turan 0000-0002-0290-5298

Mehmet Ali Cengiz 0000-0002-1271-2588

Proje Numarası PYO. SCIENCE. 1904.17.004
Yayımlanma Tarihi 1 Ekim 2020
Gönderilme Tarihi 5 Nisan 2020
Kabul Tarihi 23 Ağustos 2020
Yayımlandığı Sayı Yıl 2020

Kaynak Göster

APA Turan, S. C., & Cengiz, M. A. (2020). Determining the Factors that Influence the Effectiveness of the Health Sector in the OECD Countries. Sakarya University Journal of Science, 24(5), 1094-1104. https://doi.org/10.16984/saufenbilder.714736
AMA Turan SC, Cengiz MA. Determining the Factors that Influence the Effectiveness of the Health Sector in the OECD Countries. SAUJS. Ekim 2020;24(5):1094-1104. doi:10.16984/saufenbilder.714736
Chicago Turan, Selin Ceren, ve Mehmet Ali Cengiz. “Determining the Factors That Influence the Effectiveness of the Health Sector in the OECD Countries”. Sakarya University Journal of Science 24, sy. 5 (Ekim 2020): 1094-1104. https://doi.org/10.16984/saufenbilder.714736.
EndNote Turan SC, Cengiz MA (01 Ekim 2020) Determining the Factors that Influence the Effectiveness of the Health Sector in the OECD Countries. Sakarya University Journal of Science 24 5 1094–1104.
IEEE S. C. Turan ve M. A. Cengiz, “Determining the Factors that Influence the Effectiveness of the Health Sector in the OECD Countries”, SAUJS, c. 24, sy. 5, ss. 1094–1104, 2020, doi: 10.16984/saufenbilder.714736.
ISNAD Turan, Selin Ceren - Cengiz, Mehmet Ali. “Determining the Factors That Influence the Effectiveness of the Health Sector in the OECD Countries”. Sakarya University Journal of Science 24/5 (Ekim 2020), 1094-1104. https://doi.org/10.16984/saufenbilder.714736.
JAMA Turan SC, Cengiz MA. Determining the Factors that Influence the Effectiveness of the Health Sector in the OECD Countries. SAUJS. 2020;24:1094–1104.
MLA Turan, Selin Ceren ve Mehmet Ali Cengiz. “Determining the Factors That Influence the Effectiveness of the Health Sector in the OECD Countries”. Sakarya University Journal of Science, c. 24, sy. 5, 2020, ss. 1094-0, doi:10.16984/saufenbilder.714736.
Vancouver Turan SC, Cengiz MA. Determining the Factors that Influence the Effectiveness of the Health Sector in the OECD Countries. SAUJS. 2020;24(5):1094-10.

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