Purpose/Objectives: Since the start of the Syrian war, a significant population has moved out of the Syrian Republic into its neighborhood environs.
Turkey has had a significant effect on its health system and society, as a significant new number has entered the Turkish society, increasingly
using the Turkish healthcare system. Our aim is not only to numerically identify the size of the effect to the Turkish system, but to identify the
domestic resources that allow the Turkish healthcare system and society to build up resilience against the significant health demand shock. The
main objectives of this study is 1) To understand whether there is a complementarity between the earlier efforts in the Turkish health system and
the current capabilities that is necessary to meet the Syrian Populations Health Needs. 2) To understand if the newly revamped Turkish Primary
Healthcare System Provide a crucial buffer for the negative congestion effects that could have been caused by such a significant and relatively
unhealthy refugee population being integrated into the health system, at a relatively rapid pace.
Research method: The main two outcomes that the analysis plans to predict are the changing efficiency and the changing user satisfaction of the
Turkish health system. Using multi-level regression models (MLO) we (i) Start by looking at the effect of the Syrian effect on the crucial Turkish health
parameters, following this by (ii) Looking at the factors of family health program introduction, and family health system utilization to look at how
the functionality of the health system, and the satisfaction that it brings to the Turkish population is being affected. We used fixed effect model
to remove unobserved heterogeneity in each province (model specification in Appendix 1). We have controlled for health system variables (public
primary physicians per 10,000; public hospital specialists per 10,000; public hospitals per 10,000; public PHC centres per 10,000; and the presence of
a university hospital in the province) as well as population characteristics (rural population (%); population aged 65 and over (%); population aged 14
and under (%); and the province population). Because demographic data was available only for the years 2007-12, it was linearly extrapolated for the
years 2002-6 and 13. The penetration of family medicine model in each province was measured by an indicator variable (0,1) for whether the MLO
model was introduced, and the number of years since the introduction of the MLO model. The Syrian effect was measured through the proportion
of Syrians under temporary protection status to the domestic province population.
Main results: The health system status of the Turkish population is unaffected in the large period from 2011-2016. The significant effect in the
initial period was significantly alleviated in the intervening years. The main sources of resilience were found to be the changing importance of the
alternative primary health system that allowed Turks to receive a new option to the secondary part of the Turkish health system that was increasingly
congested. Increasing use of the immunization for the same goal is also substantiated for the Turkish population.
Recommendations: Turkey’s experience is instructive for a lot of the middle income countries, which can face similar refugee and migrant pressure
in the next 50 years. The health systems priority to UHC and to (relative) open access that it offered to its citizen population and its outside
populations alike, has served its efficacy in good stead. The health system must create enough elasticity to limit a drop in health system satisfaction
and health system utilization in either of these critical populations.