An empirical study of comparing DEA and SFA methods to measure hospital units' efficiency

Abstract

The paper aims to examine the data envelopment analysis (DEA) and stochastic frontier analysis (SFA) results in order to facilitate a common understanding about the adequacy of these methods, defining any differences in healthcare efficiency estimation. A two-stage bootstrap DEA method and the Translog formula of the SFA were performed. Multi-inputs and multi-outputs were used in both of the approaches assuming two scenarios either including environmental variables or not. Thirty-two Greek public hospital units constitute the sample. DEA and SFA were found to yield divergent efficiency estimates due to many factors such as the nature of the environmental variables, the measurement error and other random factors. Environmental variables being hospital status and geographical position were found significantly correlating with inefficiency. The analysis concludes that the choice of the appropriate mathematical form depends on the expertise of the researcher and the purpose of the evaluation.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 35 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.