Research Article
PDF Mendeley EndNote BibTex Cite

Tıbbi Kaynaklar Açısından OECD Ülkelerinin Hiyerarşik Kümeleme Analizi ile Sınıflandırılması

Year 2022, Volume 00, Issue , 21.03.2022
https://doi.org/10.20515/otd.978341

Abstract

Tıbbı kaynakların kullanımına ilişkin veriler önemli sağlık göstergeleri arasında kabul edilir. Dünya Bankası verilerini kullanarak Ekonomik İşbirliği ve Kalkınma Teşkilatı (OECD) üye ülkelerini tıbbi kaynaklar ve bunların kullanımı açısından sınıflandırmayı amaçladık. Bu araştırma kesitsel tipte bir çalışma olup; 2010-2015 yılları arasındaki tıbbi kaynaklar ve bunların kullanım verileri değerlendirildi. OECD üyesi 36 ülke arasından veri eksikliği olan 13 ülke çalışmaya dahil edilemedi. Tıbbi kaynaklar ve bunların kullanımı açısından benzerlik gösteren ülkeleri saptayarak gruplayabilmek için hiyerarşik kümeleme analizi kullanıldı. Hiyerarşik kümeleme analizinin çeşitli yöntemleri olmasına rağmen Ward yöntemi kullanılmıştır. Ward yöntemiyle kümeler elde etmek için Kare Öklid mesafesi kullanıldı. Değişkenler arasındaki ilişkiyi değerlendirmek için Pearson korelasyon analizi kullanıldı. Hiyerarşik kümeleme analizi ile seçilmiş olan 23 OECD ülkesi 4 kümeye ayrıldı. Türkiye'nin İsrail, İspanya, Yunanistan ve Meksika ile birlikte ilk kümede yer aldığı tespit edildi. Sağlık göstergeleri açısından OECD ülkeleri arasındaki heterojen kümelenme, ülkeler arasındaki finansal eşitsizlik başta olmak üzere birçok faktörden kaynaklanmış olabilir. Olası faktörlerin net bir şekilde ortaya konabilmesi için daha ayrıntılı çalışmalar yapılmasına ihtiyaç duyulmaktadır

References

  • 1. Commission E. European Core Health Indicators [Available from: https://ec.europa.eu/health/indicators/echi/list_en.
  • 2. Bank W. Health, Nutrition and Population [27.05.2019]. Available from: http://datatopics.worldbank.org/health/available-indicators.
  • 3. OECD. about [Available from: https://www.oecd.org/about/.
  • 4. Varabyova Y, Müller J-M. The efficiency of health care production in OECD countries: A systematic review and meta-analysis of cross-country comparisons. Health Policy. 2016;120(3):252-63.
  • 5. Buchan J, O'may F, Dussault G. Nursing workforce policy and the economic crisis: a global overview. Journal of Nursing Scholarship. 2013;45(3):298-307.
  • 6. Kimes PK, Liu Y, Neil Hayes D, Marron JS. Statistical significance for hierarchical clustering. Biometrics. 2017;73(3):811-21.
  • 7. Arah OA, Westert GP, Hurst J, Klazinga NS. A conceptual framework for the OECD health care quality indicators project. International Journal for Quality in Health Care. 2006;18(suppl_1):5-13.
  • 8. De Looper M, Lafortune G. Measuring disparities in health status and in access and use of health care in OECD countries. 2009.
  • 9. OECD. HEALTH AT A GLANCE: Europe 2018: ORGANIZATION FOR ECONOMIC; 2018.
  • 10. Organisation WH. Global Health Observatory (GHO) data 2019 [26.06.2019]. Available from: https://www.who.int/gho/publications/world_health_statistics/en/.
  • 11. OCDE SS, Hurst J. The supply of physician services in OECD countries. OECD health working papers.
  • 12. Retzlaff-Roberts D, Chang CF, Rubin RM. Technical efficiency in the use of health care resources: a comparison of OECD countries. Health policy. 2004;69(1):55-72.
  • 13. Bank TW. GDP per capita (current US$) 2019 [Available from: https://data.worldbank.org/indicator/ny.gdp.pcap.cd.
  • 14. VEHİD S. TEMEL DEMOGRAFİK ve SAĞLIK DÜZEYİ ÖLÇÜTLERİ AÇISINDAN TÜRKİYE İLE AVRUPA BİRLİĞİ'NE (AB) ÜYE ÜLKELERİN KARŞILAŞTIRILMASI. Cerrahpaşa Tıp Dergisi.31(2).
  • 15. Buchan J, Twigg D, Dussault G, Duffield C, Stone P. Policies to sustain the nursing workforce: an international perspective. International nursing review. 2015;62(2):162-70.
  • 16. OECD. OECD Health Statistics 2019 [Available from: https://www.oecd-ilibrary.org/social-issues-migration-health/data/oecd-health-statistics_health-data-en.
  • 17. Karanikolos M, Mladovsky P, Cylus J, Thomson S, Basu S, Stuckler D, et al. Financial crisis, austerity, and health in Europe. The Lancet. 2013;381(9874):1323-31.

Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis

Year 2022, Volume 00, Issue , 21.03.2022
https://doi.org/10.20515/otd.978341

Abstract

Medical resources and usage data collected regularly and could be considered a major benchmark for countries. We aimed to classify the Organisation for Economic Co-operation and Development(OECD) member countries using the World Bank data in terms of medical resources and usage. This is a cross - sectional study. The medical resources and usage data between 2010-2015 were evaluated. Among 36 OECD member countries, 13 of them that lacked data couldn’t be included in the study. Hierarchical clustering analysis was used for grouping countries with similar medical resources and usage. Although there are various methods of hierarchical clustering analysis, Ward method, has been used. Square Euclidean distance was used to obtain clusters by Ward method. Pearson correlation analysis was used to evaluate the relationship between variables. Hierarchical clustering analysis resulted in 4 clusters for selected 23 OECD countries. It was found that Turkey was in the first cluster together with Israel, Spain, Greece and Mexico. The heterogeneous clustering among the OECD countries may have been produced by the financial disparities between the countries. The results are expected to provide helpful insight on the comparison of health status.

References

  • 1. Commission E. European Core Health Indicators [Available from: https://ec.europa.eu/health/indicators/echi/list_en.
  • 2. Bank W. Health, Nutrition and Population [27.05.2019]. Available from: http://datatopics.worldbank.org/health/available-indicators.
  • 3. OECD. about [Available from: https://www.oecd.org/about/.
  • 4. Varabyova Y, Müller J-M. The efficiency of health care production in OECD countries: A systematic review and meta-analysis of cross-country comparisons. Health Policy. 2016;120(3):252-63.
  • 5. Buchan J, O'may F, Dussault G. Nursing workforce policy and the economic crisis: a global overview. Journal of Nursing Scholarship. 2013;45(3):298-307.
  • 6. Kimes PK, Liu Y, Neil Hayes D, Marron JS. Statistical significance for hierarchical clustering. Biometrics. 2017;73(3):811-21.
  • 7. Arah OA, Westert GP, Hurst J, Klazinga NS. A conceptual framework for the OECD health care quality indicators project. International Journal for Quality in Health Care. 2006;18(suppl_1):5-13.
  • 8. De Looper M, Lafortune G. Measuring disparities in health status and in access and use of health care in OECD countries. 2009.
  • 9. OECD. HEALTH AT A GLANCE: Europe 2018: ORGANIZATION FOR ECONOMIC; 2018.
  • 10. Organisation WH. Global Health Observatory (GHO) data 2019 [26.06.2019]. Available from: https://www.who.int/gho/publications/world_health_statistics/en/.
  • 11. OCDE SS, Hurst J. The supply of physician services in OECD countries. OECD health working papers.
  • 12. Retzlaff-Roberts D, Chang CF, Rubin RM. Technical efficiency in the use of health care resources: a comparison of OECD countries. Health policy. 2004;69(1):55-72.
  • 13. Bank TW. GDP per capita (current US$) 2019 [Available from: https://data.worldbank.org/indicator/ny.gdp.pcap.cd.
  • 14. VEHİD S. TEMEL DEMOGRAFİK ve SAĞLIK DÜZEYİ ÖLÇÜTLERİ AÇISINDAN TÜRKİYE İLE AVRUPA BİRLİĞİ'NE (AB) ÜYE ÜLKELERİN KARŞILAŞTIRILMASI. Cerrahpaşa Tıp Dergisi.31(2).
  • 15. Buchan J, Twigg D, Dussault G, Duffield C, Stone P. Policies to sustain the nursing workforce: an international perspective. International nursing review. 2015;62(2):162-70.
  • 16. OECD. OECD Health Statistics 2019 [Available from: https://www.oecd-ilibrary.org/social-issues-migration-health/data/oecd-health-statistics_health-data-en.
  • 17. Karanikolos M, Mladovsky P, Cylus J, Thomson S, Basu S, Stuckler D, et al. Financial crisis, austerity, and health in Europe. The Lancet. 2013;381(9874):1323-31.

Details

Primary Language English
Subjects Health Care Sciences and Services
Journal Section ORİJİNAL MAKALE
Authors

Gökçe DAĞTEKİN (Primary Author)
uşak il sağlık müdürlüğü
0000-0002-6424-2434
Türkiye


Ali KILINÇ
ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ
0000-0002-0577-8570
Türkiye


Ertugrul COLAK
ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ
0000-0003-3251-1043
Türkiye


Alaettin ÜNSAL
ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ
0000-0001-8353-1605
Türkiye


Didem ARSLANTAS
ESKİŞEHİR OSMANGAZİ ÜNİVERSİTESİ
0000-0002-5263-3710
Türkiye

Supporting Institution yoktur
Publication Date March 21, 2022
Published in Issue Year 2022, Volume 00, Issue

Cite

Bibtex @research article { otd978341, journal = {Osmangazi Tıp Dergisi}, issn = {1305-4953}, eissn = {2587-1579}, address = {}, publisher = {Eskişehir Osmangazi University}, year = {2022}, volume = {00}, pages = { - }, doi = {10.20515/otd.978341}, title = {Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis}, key = {cite}, author = {Dağtekin, Gökçe and Kılınç, Ali and Colak, Ertugrul and Ünsal, Alaettin and Arslantas, Didem} }
APA Dağtekin, G. , Kılınç, A. , Colak, E. , Ünsal, A. & Arslantas, D. (2022). Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis . Osmangazi Tıp Dergisi , 00 , . DOI: 10.20515/otd.978341
MLA Dağtekin, G. , Kılınç, A. , Colak, E. , Ünsal, A. , Arslantas, D. "Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis" . Osmangazi Tıp Dergisi 00 (2022 ): <https://dergipark.org.tr/en/pub/otd/issue/35590/978341>
Chicago Dağtekin, G. , Kılınç, A. , Colak, E. , Ünsal, A. , Arslantas, D. "Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis". Osmangazi Tıp Dergisi 00 (2022 ):
RIS TY - JOUR T1 - Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis AU - Gökçe Dağtekin , Ali Kılınç , Ertugrul Colak , Alaettin Ünsal , Didem Arslantas Y1 - 2022 PY - 2022 N1 - doi: 10.20515/otd.978341 DO - 10.20515/otd.978341 T2 - Osmangazi Tıp Dergisi JF - Journal JO - JOR SP - EP - VL - 00 IS - SN - 1305-4953-2587-1579 M3 - doi: 10.20515/otd.978341 UR - https://doi.org/10.20515/otd.978341 Y2 - 2021 ER -
EndNote %0 Osmangazi Journal of Medicine Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis %A Gökçe Dağtekin , Ali Kılınç , Ertugrul Colak , Alaettin Ünsal , Didem Arslantas %T Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis %D 2022 %J Osmangazi Tıp Dergisi %P 1305-4953-2587-1579 %V 00 %N %R doi: 10.20515/otd.978341 %U 10.20515/otd.978341
ISNAD Dağtekin, Gökçe , Kılınç, Ali , Colak, Ertugrul , Ünsal, Alaettin , Arslantas, Didem . "Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis". Osmangazi Tıp Dergisi 00 / (March 2022): - . https://doi.org/10.20515/otd.978341
AMA Dağtekin G. , Kılınç A. , Colak E. , Ünsal A. , Arslantas D. Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis. Osmangazi Tıp Dergisi. 2022; 00: -.
Vancouver Dağtekin G. , Kılınç A. , Colak E. , Ünsal A. , Arslantas D. Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis. Osmangazi Tıp Dergisi. 2022; 00: -.
IEEE G. Dağtekin , A. Kılınç , E. Colak , A. Ünsal and D. Arslantas , "Classification of Oecd Countries in Terms of Medical Resources and Usage with Hierarchical Clustering Analysis", Osmangazi Tıp Dergisi, vol. 00, Mar. 2022, doi:10.20515/otd.978341

13299         13287  13308       13306       13305    13307  13301