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Öğe A systematic approach to identify health system resilience indicators using artificial neural network algorithm(2024) Çakır, Kübra; Erol, Özgür; Arslan Öztürk, HaticeAccording to the World Health Organization (WHO), a health system comprises all organizations, people, and actions that aim to promote, restore, or maintain health [1]. Health systems perform multiple functions in society not only delivering healthcare services and other interventions aimed at maintaining or improving health. They serve multiple societal functions beyond merely delivering healthcare services, but also adapting to risks, disasters, and unpredictable events to maintain functionality. Health system resilience, therefore, refers to the system's capacity to adapt and return to previous performance levels as quickly as possible after such disruptions. The WHO has created a model called Six Building Blocks to measure the health system's resilience. This study aims to assign indicators obtained from a comprehensive literature review to the blocks established by the World Health. The study uses an Artificial Neural Network (ANN) algorithm to analyze data from 35 Organisation for Economic Co-Operation and Development (OECD) countries from 2020 to 2022. ANN is used to assess the varied relevance or weights of each building block's contribution to health system resilience, providing detailed knowledge of how different components impact overall health system performance during crises. As a consequence of this study, policymakers may identify which healthcare building block and accompanying indicator should be prioritized for investment in preparation for future pandemics. The findings suggest which characteristics are most important for increasing health system resilience during public health emergencies.Öğe Measuring health systems resilience: A comparative study of Turkey's health system during COVID-19 Pandemic(Institute of Electrical and Electronics Engineers Inc., 2022) Erol Yeşilsırt, Özgür; Tozan, Hakan; Çakır, Kübra; Do?an, İdil; Bacacı, Firdevs DilaraThe recent outbreak of the COVID-19 pandemic has drawn significant attention to the topic of health-system resilience. Many countries have taken certain measures to deal with the negative outcomes of the pandemic and to improve their health systems. Having a resilient health system during pandemics ensures the continuity and success of healthcare services. Resilience, as a concept, represents a proactive rather than a reactive approach to overcoming the negative outcomes of disasters. Understanding the characteristics of a resilient health system will help to strengthen the health systems for future pandemics or any other disasters. In this research project, characteristics of resilient health systems are investigated using a framework based on three main dimensions of systems resilience: (1) a system's capability to decrease its level of vulnerability to expected and unexpected disruptive events, (2) its ability to change itself and adapt to the changing environment; (3) its ability to recover in the least possible time in case of a disruptive event. Based on this framework, four attributes of resilience are identified, namely agility, adaptability, flexibility, and vulnerability. Further, these attributes of resilience are evaluated using country-specific COVID-19-related qualitative and quantitative data from Turkey and compared with several other countries. Suggestions and further recommendations are provided on how to measure and improve the resiliency of health systems for future pandemics.Öğe A polyurethane/carbon black composite absorber for low frequency waves(Springer-Verlag Berlin, 2019) Yağımlı, Mustafa; Tozan, Hakan; Esen, H. Ergin; Arca, EminThis study proposes a Polyurethane/Carbon Black composite coating that has the ability of absorbing low frequency waves. The characteristics of coating including contact angle measurements are provided and for performance analyses, a 1 kHz amplitude-modulated signal superimposed on red and green laser beam (whose intensity is changed by square wave) sent to composite coated surface. The reflected beam from the coating was detected by BPW20RF photodetector and signal waves were measured. The results of the analyses illustrated that the composite; coating to a great extent, absorbed the waves.Öğe Defining criteria weights by ahp in health technology assessment(Elsevier Sciences, 2017) Örtürk, N.; Karacan, İlknur; Tozan, Hakan; Vayvay, ÖzalpObjectives: Multi Criteria Decision Making (MCDM) is claimed to be the aid for Health Technology Assessment (HTA) based decision making. Transparent commitment of multi-disciplinary stakeholders is essential to attain public confidence in healthcare decision making. In current deliberative process commitment of stakeholders is not transparent. This research aims to propose a prioritization approach for MCDM applications in HTA by Analytic Hierarchy Process (AHP).
