An integrated quality and resilience engineering framework in healthcare with Z-number data envelopment analysis

Abstract

Supplier selection for medical equipment is a major challenge for hospitals in healthcare supply chains. The primary reason for measuring medical equipment supplier efficiency is to achieve the highest level of overall performance and productivity in healthcare supply chains. This study presents an integrated quality and resilience engineering (QRE) framework for evaluating medical equipment suppliers' performance using structural equation modeling and Z-number data envelopment analysis (Z-DEA). Noise analysis is used to select the best α-cut for the Z-DEA model, and fuzzy data are used to handle uncertainties. We show that flexibility, conformance to standards, redundancy, cost, quality certifications, and delivery time significantly affect the medical equipment suppliers' performance. In addition, we demonstrate that the proposed integrated QRE framework is more efficient and informative than stand-alone quality engineering or resiliency engineering. We present a case study in a cardiovascular hospital to illustrate the applicability of the proposed framework for medical equipment supplier evaluation and selection. To the best of our knowledge, this is the first study to integrate QRE and Z-DEA for supplier performance evaluation in healthcare.

Keywords: Data envelopment analysis; Fuzzy set; Healthcare; Quality and resilience engineering; Supplier evaluation; Z-number.