Purpose: The study aims to evaluate the capacity and capacity gaps of the Turkish health system at the provincial level in relative terms. The secondary objective of the study is to develop application algorithms for the weighting methods utilized in the R programming language. Methodology: The decision criteria used in evaluation of health system capacity were weighted by CRITIC, Shannon Entropy, and NMV methods. The WISP method was used to evaluate the health system capacity of provinces. Data were drawn from the Ministry of Health's Health Statistics Yearbook for 2022. Findings: Tunceli, Bayburt, and Kilis are the three provinces closest to the optimal solution among 81 provinces in terms of health system capacity in Türkiye, according to CRITIC-based WISP scores. On the contrary, Bursa, İstanbul and Şanlıurfa are the three provinces furthest from an optimal solution. Originality: At the provincial level, gaps in the health system's capacity can be identified and subsequently improved. It is possible to develop self-sufficient health system capacity and enhance its resilience. The development of application algorithms for weighting methods makes a significant contribution. Decision makers are capable of generating immediate solutions for both small and large-scale data sets using the algorithms.
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