Cross-efficiency evaluation in the presence of flexible measures with an application to healthcare systems

Sepideh Abolghasem, Mehdi Toloo*, Santiago Amézquita

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)


In recent years, most countries around the world have struggled with the consequences of budget cuts in health expenditure, obliging them to utilize their resources efficiently. In this context, performance evaluation facilitates the decision-making process in improving the efficiency of the healthcare system. However, the performance evaluation of many sectors, including the healthcare systems, is, on the one hand, a challenging issue and on the other hand a useful tool for decision- making with the aim of optimizing the use of resources. This study proposes a new methodology comprising two well-known analytical approaches: (i) data envelopment analysis (DEA) to measure the efficiencies and (ii) data science to complement the DEA model in providing insightful recommendations for strategic decision making on productivity enhancement. The suggested method is a first attempt to combine two DEA extensions: flexible measure and cross-efficiency. We develop a pair of benevolent and aggressive scenarios aiming at evaluating cross-efficiency in the presence of flexible measures. Next, we perform data mining cluster analysis to create groups of homogeneous countries. Organizing the data in similar groups facilitates identifying a set of benchmarks that perform similarly in terms of operating conditions. Comparing the benchmark set with poorly performing countries we can obtain attainable goals for performance enhancement which will assist policymakers to strategically act upon it. A case study of healthcare systems in 120 countries is taken as an example to illustrate the potential application of our new method.

Original languageEnglish
Pages (from-to)512-533
Number of pages22
JournalHealth Care Management Science
Issue number3
Publication statusPublished - Sept 15 2019
Externally publishedYes


  • Clustering
  • Cross-efficiency
  • Data envelopment analysis
  • Data science
  • Flexible measure
  • Healthcare

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • General Health Professions

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