Performance and congestion analysis of the portuguese hospital services

Abstract

The health care services have been characterised by a growing demand by the citizens leading to the need of more and more resources. Population aging, new pathologies and drugs as well as new treatments are some of the major factors for this. However, in hospitals, for example, consumption of a large number of inputs frequently has not corresponded to the production of the same or more proportion of outputs. Sometimes, the outputs even decline with the increase of inputs due to the influence of the congestion effect on efficiency. The heavy burden of the health sector on the state budget brings about the interest of research over its efficiency. This paper aims to assess the performance of the Portuguese hospitals and particularly the contribution of the congestion effect. We use the non-parametric technique of data envelopment analysis (DEA) for this purpose and a double-bootstrap procedure to take into account the influence of operational environment on efficiency. Afterwards, by comparing three different approaches we determine the importance of congestion in efficiency measurement and discuss its computation methodologically. The results suggest significant levels of inefficiency in 68 major Portuguese hospitals for the year 2005 and more than half of them were found to be congested.

Estimating the efficiency of Portuguese hospitals using an appropriate production technology

“…This proves that governmental reforms are failing since agglomeration was seen as a means of improving efficiency. These results are in line with previous studies (Simões and Marques, ). Regarding efficiency growth, both models indicate a large increase in efficiency of the HC) and a reduction in efficiency of LHU especially from 2006 to 2007 (Fig.…”

Data Envelopment Analysis for Relative Efficiency Measurement of Chinese Hospitals: A Systematic Review

“…Novel applications and extensions of efficiency measurement in two stages includes DEA with Tobit (Fareed et al, 2012;Kirigia & Asbu, 2013;Nayar et al, 2013), multiple (Bates et al, 2006;Gok & Sezen, 2013), logistic (Chustz, 2012;Lobo et al, 2014) and truncated regression analysis (Araujo et al, 2014;Halkos & Tzeremes, 2011;Kounetas & Papathanassopoulos, 2013;Mitropoulos et al, 2013), etc. Furthermore, a considerable extended DEA models have been developed in international studies, including bootstrap-DEA (Halkos & Tzeremes, 2011;Puenpatom & Rosenman, 2008;Simões & Marques, 2011;Varabyova & Schreyogg, 2013), congestion-DEA (Ferrier et al, 2006;Masiye, 2007;Valdmanis et al, 2004;Valdmanis et al, 2008), DEA-R (Wei et al, 2011), post DEA cross-evaluation and cluster analysis (Flokou et al, 2011), and multi-criteria DEA models (Ajlouni et al, 2013;Zaim et al, 2007), etc.…”

Congestion analysis to evaluate the efficiency and appropriateness of hospitals in Sicily

“…Clement et al [17] used output-congestion analysis on data drawn from patient-level discharge and hospital-level organizational data from 10 U.S. states in 2000. More recently, Simões and Marques [18] performed the input-congestion analysis of 68 Portuguese hospitals, in order to study the output decline which is associated with the increase of inputs. They measured the congestion effect by using three alternative methods.…”