Clustering and ranking analysis with imprecise data for evaluating healthcare performance of districts in Istanbul

Abstract

Over the past decade, healthcare has been one of the fastest growing sectors both in developed and developing countries. One of the main targets of most countries is to improve their healthcare system in terms of service quality and efficiency, where Turkey is no exception. This paper presents an imprecise data envelopment analysis (DEA)-based approach for clustering and ranking of 26 districts in Istanbul, the most crowded city of Turkey. The proposed methodology determines subgroups of districts operating under similar circumstances, and provides ranking of 26 districts as well as the best performing district in Istanbul in terms of healthcare utilizing data from state hospitals.