Türkiye’nin toplam sağlık harcaması tahmini için trend-artık ayrıştırması temelli bir modelleme yaklaşımı
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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Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Veri Modelleri, Depolama ve Dizinleme, Evrimsel Hesaplama, Modelleme ve Simülasyon |
| Bölüm | Makaleler |
| Yazarlar | |
| Erken Görünüm Tarihi | 17 Mayıs 2024 |
| Yayımlanma Tarihi | 20 Mayıs 2024 |
| Gönderilme Tarihi | 20 Haziran 2023 |
| Kabul Tarihi | 9 Aralık 2023 |
| Yayımlandığı Sayı | Yıl 2024 Cilt: 39 Sayı: 4 |