Sağlık Kaynakları için Tam Sayılı Yanıt Optimizasyon Modellerinin Uygulanması

Year 2023, Volume: 7 Issue: 1, 81 - 93, 02.01.2024

Abdulkadir Atalan

https://doi.org/10.26650/acin.1096774

Abstract

Bu çalışma, Türk sağlık sistemindeki hastane sayısı ile sağlık profesyonelleri arasındaki ilişkiyi araştırmak amacıyla yapılmıştır. Çalışma verileri 1967-2018 yıllarını kapsamaktadır. Çalışmada istatistiksel analizler yapılmış ve lineer regresyon yanıt optimizasyon modelleri kullanılarak tamsayılı yanıt optimizasyon modelleri oluşturulmuştur. Karar değişkenleri arasındaki ilişkiyi göstermek için Pearson korelasyon testi uygulanmıştır. Doğrusal regresyon modeli ile belirlenen yanıt değişkeninin varyasyon yüzdesi 97,85 olarak hesaplanmıştır. Hemşire (p değeri=0,001, f değeri=21,36, t değeri=-4,62), ebe (p değeri=0,001, f değeri=24,88, t değeri=4,99) ve diğer sağlık çalışanları (DSÇ) (p değeri=0,001, f değeri = 24.16, t değeri=4.92) hastane sayısı üzerinde etkili bulunmuş, doktor ve eczacı hastane sayısı üzerinde %1.00 veya %5.00 hata payı ile etkili olmamıştır. 1798 hastanede sağlık hizmeti vermek için gereken optimum sağlık çalışanı sayısı 153128 doktor, 165244 hemşire, 56351 ebe, 32032 eczacı ve 177409 DSÇ olarak hesaplanmıştır. Bu çalışmanın sonucunda, Türk hükümetinin sağlık sisteminin mevcut kaynakları ile daha fazla hastanede sağlık hizmeti sunabilmesi gerektiği doğrulanmıştır.

Keywords

Türk Sağlık Sistemi, Sağlık Profesyonelleri, Hastaneler, Tamsayılı Yanıt Optimizasyon Modelleri

Application of Integer Response Optimization Models for the Healthcare Resources

Abstract

This study investigated the relationship between the number of hospitals and healthcare professionals in the Turkish healthcare system. The study data covers the years 1967-2018. In the study, statistical analysis was performed, and the integer response optimization models were created using the linear regression response optimization models. The Pearson correlation test was applied to show the relationship between decision variables. The percentage of variation of the response variable specified by the linear regression model was calculated as 97.85. The numbers of nurses (p value=0.001, f value=21.36, t value=-4.62), midwives (p value=0.001, f value=24.88, t value=4.99), and OHP (Other health professionals) (p value=0.001, f value=24.16, t value=4.92) were found to be effective on the number of hospitals, doctors and pharmacists were not effective on the number of hospitals with a margin of error of 1.00% or 5.00%. The optimum number of healthcare workers required to provide health services in 1798 hospitals was calculated as 153128 doctors, 165244 nurses, 56351 midwives, 32032 pharmacists, and 177409 OHP. As a result of this study, we confirmed that the Turkish government should be able to provide health services in more hospitals with the existing healthcare system resources.

Keywords

Turkish Healthcare System, Healthcare Professionals, Hospitals, Integer Response Optimization Models

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