Severity of illness in the case-mix specification and performance: A study for Italian public hospitals

Abstract

Background: Public hospitals’ expenditures in Italy is approximately 45% of total public health financing. The reduction of public debt requires reducing total public health, as well as hospital expenditures in the public sector. Past health reforms introduced rules to improve the efficiency in controlling hospital costs with a better use of resources. The objective of this study is to derive technical efficiency as a performance measurement in the directly managed public hospitals in Italy under different case-mix specifications, as well as to discover the effect of it on technical efficiency.

Methods: Two different Data Envelopment Analysis (DEA) models are solved. To control for the influence of the case-mix complexity/severity of illness on technical efficiency, the distributions of DEA efficiency scores are compared applying statistical tests developed in the non-parametric efficiency analysis.

Results: On average, in the year 2007, the technical efficiency in the sample is lower (0.8071) in model B (output mix with weighted Case Mix Index) than in model A (0.8748). The bootstrap-corrected efficiency scores of models B and A are respectively 0.7185 and 0.8106. On average, the case mix index in the sample is 0.87859. Statistical tests confirm that the differences in the efficiency scores distribution are statistically significant, confirming that treatment complexity has influenced technical efficiency. At the individual hospital level, the effect is more evident, modifying the rank and the technical efficiency of the hospitals.

Conclusions: The different case-mix specifications adjusted with Case Mix Index, generate statistically significant differences in the distribution of the efficiency scores. This evidence permits us to conclude that the performance
of the Local Health Trust’s directly managed public Italian hospitals is influenced by the hospitals’ case-mix severity/complexity. As a policy indication, we can observe that the need for policy makers and hospital managers to reduce hospital costs conflicts with the need to guarantee an optimum level of hospital resources with different case-mix complexities of the treated cases.