Turkiye Klinikleri Journal of Biostatistics

.: ORIGINAL RESEARCH
Türkiye'de 2003-2016 Yılları Arasında Temel Sağlık Göstergelerinin Joinpoint Regresyon Yöntemi ile Analizi
Joinpoint Regression Analysis of the Basic Health Indicators Between the Years of 2003-2016 in Turkey
Pakize YİĞİTa, Seda KUMRUb
aBiyoistatistik ve Tıp Bilişimi, AD, Istanbul Medipol Üniversitesi Tıp Fakültesi,
bSağlık Yönetimi AD, İstanbul Medipol Üniversitesi Sağlık Bilimleri Fakültesi, İstanbul, TÜRKİYE
Turkiye Klinikleri J Biostat. 2019;11(1):47-65
doi: 10.5336/biostatic.2018-63898
Article Language: TR
Full Text
ÖZET
 Amaç: Klasik regresyon analizi modeli incelenen dönem içerisinde trendin değişmediğini varsayar. Fakat, epidemiyolojik araştırmalarda çeşitli yapısal değişimler, risk faktörleri, politikaların değişmesi gibi müdaheleler ile sağlık göstergeleri incelenen dönem için sabit bir trende sahip olmayabilir. Çalışılan zamanda meydana gelen bu parçalı trendleri bulabilmek için Joinpoint Regresyon Analizi (JRA) kullanılmaktadır. JRA zamanda meydana gelen bu kırılmalar için kısa dönem trendleri ve bu parçalı trendlerden geometrik ortalama ile uzun dönem trendleri hesaplar. Bu çalışmanın amacı, sağlık bakanlığının 2003 yılından başlayarak sağlıkta dönüşüm adı altında geliştirdiği reformların sağlık göstergelerinde meydana getirdiği değişimleri JRA ile analiz etmektir. Gereç ve Yöntemler: Bu kapsamda, 2003-2016 yılları arasında Dünya Sağlık Örgütü'nün (DSÖ) sağlık statüsü, risk faktörleri, sağlık hizmetleri kapsamı, sağlık sistemi başlığı altındaki 15 değişkeni JRA ile test etmektir. Bulgular: Bebek ölüm hızında 2003-2010 döneminde yıllık % 12.8 anlamlı düşüş (p<0.001), 2010-2016 yıllarında ise yıllık %2.8 anlamlı olmayan (p=0.147) düşüş olduğu görülmüştür. Hemşire sayısında, 2005-2012?de yıllık % 6.6 (p<0.001), 2012-2016?da yıllık % 0.8 (p=0.049) anlamlı artış, hekim sayısının ise incelenen dönemde yıllık ortalama % 2.1 anlamlı artış gösterdiği hesaplanmıştır(p<0.001). Sonuç: OECD ülkeleri ile karşılaştırıldığında da sağlık göstergelerinin iyileştirilebilmesi için özellikle bebek ölüm hızı ve sağlık çalışanları göstergelerinde ortalamanın altında kalındığı ve bu alanlara odaklanan sağlık politikalarının uygulanması gerektiği düşünülmektedir.

Anahtar Kelimeler: Joinpoint regresyon; sağlık göstergeleri; yapısal kırılma; zaman serileri analizi
ABSTRACT
 Objective: Classical regression analysis model assumes that trend remain constant in the given time scale. However, in epidemiological research, due to some involvements such as structural changes, risk factors and changes in policies, health indicators may not remain constant in the given time scale. In order to locate these segmented trends on the time scale Joinpoint Regression Analysis (JRA) is used. JRA employs Annual Percent Change (APC) to locate these segments, and using those segmented trends, Annual Average Percent Change (AAPC) is calculated through geometric mean. The study at hand aims to analyze the changes in the health indicators brought about with the reforms carried out by the Ministry of Health since 2003. Material and Methods: In line with this, JRA is used to analyze data from the years of 2003 to 2016, retrieved from OECD database, focusing on 15 variables which were formulated with reference to categories health status, risk factors, health services coverage and healthcare system determined by World Health Organization (WHO). Results: There observed a statistically significant decrease in the infant mortality rates by 12.8% (p<0.001) between the years of 2003 and 2010. As for the years from 2010 to 2016, there is a statistically not significant decrease by 2.8 % (p=0.147). There is a statistically significant increase by 6.6 % (p<0.001) between 2005 and 2012, and 0.8% (p=0.049) between 2012 and 2016 in the number of nurses. As for the number of doctors in the given period of time, there is a statistically significant increase by 2.1% (p<0.001). Conclusion: When OECD countries are compared, in order to improve the health indicators, it is observed that Turkey is below the average in the infant mortality rates and indicators regarding healthcare professionals. These emerge as the areas of need for improvement requiring new health policies.

Keywords: Joinpoint regression; health indicators; structural break; time series
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