Incorporating preference information in a range directional composite indicator: The case of Portuguese public hospitals *

Grasping the intricacy and diversity of complex systems dealing with ever-growing amounts of data is essential to public and private institutions' continuous improvement. Composite indicators (CIs) emerge as aggregators of key performance indicators, providing a single measure that reflects those multidimensional performance aspects. One way to build such measures is based on the use of data envelopment analysis (DEA). Several DEA models can be used to generate CIs. Still, not many of them can deal concurrently with desirable and undesirable outputs, and incorporate the decision-making actors' preference information. Based on the directional 'Benefit-of-the-Doubt' model, we propose a novel approach consisting of the simultaneous use of weight restrictions and an artificial target reached via a range directional vector. The resulting CI assesses the Portuguese public hospitals' performance under two perspectives of hospital activity: users and providers. In the end, managerial and policy implications are withdrawn from the results of this study conducted in cooperation with the Portuguese Ministry of Health. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

Understanding the complexity and diversity of handling large amounts of data in complex systems is crucial for continuous improvement in institutions. Composite indicators serve as aggregators of key performance indicators reflecting multidimensional performance aspects, with some constructed using data envelopment analysis.