Türkiye’nin toplam sağlık harcaması tahmini için trend-artık ayrıştırması temelli bir modelleme yaklaşımı

Yıl 2024, , 2539 - 2550, 20.05.2024

Rezzan Yardımcı , Eşref Boğar

https://doi.org/10.17341/gazimmfd.1317413

Öz

Sağlık harcamalarının doğru tahmini, sağlık sistemleri ve politikaların sürdürülebilirliği açısından oldukça önemli bir konudur. Bu çalışma kapsamında Türkiye’nin toplam sağlık harcamasını yüksek doğrulukla tahmin etmek için trend-kalıntı ayrıştırması temelli bir model önerilmiştir. Önerilen model iki aşamalı bir tahmin prosedürüne sahiptir. İlk aşamada, polinomiyal regresyon kullanılarak sağlık harcaması zaman serisinin trendi belirlenmektedir. İkinci aşamada ise zaman serisinin trendden arındırılmış kısmını modellemek için doğrusal parametreleri en küçük kareler tahmin yöntemiyle ve doğrusal olmayan parametreleri sinir ağı algoritmasıyla optimize edilmiş bir kalıntı modeli önerilmiştir. 1999-2021 yıllarına ait sağlık harcaması verileri kullanılarak önerilen modelin performansı gri modeller, regresyon modelleri, üstel yumuşatma modelleri ve ARIMA modelleri ile karşılaştırılmıştır. 1999-2015 yıllarının eğitim 2016-2021 yıllarının ise test için kullanılmasıyla elde edilen sonuçlar, önerilen modelin diğer modellerden daha iyi modelleme ve tahmin performansına sahip olduğunu göstermektedir. Bu nedenle, 2022-2030 yılları için Türkiye’nin toplam sağlık harcaması önerilen model ile tahmin edilmiş olup 2030 yılında 2,2 trilyon TL değerine ulaşacağı öngörülmüştür.

Anahtar Kelimeler

Sağlık harcaması tahmini, zaman serisi ayrıştırması, modelleme, regresyon, sinir ağı algoritması

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