This paper aims to extend the literature on measuring efficiency in primary health care by considering the influence of quality indicators and environmental variables conjointly in a case study. In particular, environmental variables are represented by patients' characteristics and quality indicators are based on technical aspects. In order to deal with both aspects, different extensions of data envelopment analysis (DEA) methodology are applied. Specifically, we use weight restrictions to ensure that the efficiency scores assigned to the evaluated units take quality data into account, and a four-stage model to identify which exogenous variables have impact on performance as well as to compute efficiency scores that incorporate this information explicitly. The results provide evidence in support of the importance of including information about both aspects in the analysis so that the efficiency measures obtained can be interpreted as an accurate reflection of performance.
In this paper, we propose a different way of using the Malmquist index that allows us to further analyze the relative performance divergences between two groups of decision-making units (DMUs) over time when only a pseudo-panel database is available. To do this, we extend the Camanho and Dyson ( 2006) one-period Malmquist-type index (CDMI) for a pseudo-panel database with a new pseudo-panel Malmquist index (PPMI). To illustrate the methodology, we apply it to examine how the performance gap between public and private government-dependent secondary schools in the Basque Country (Spain) performed across three PISA waves (2006, 2009 and 2012). The results suggest that performance is persistently and significantly higher for private government-dependent schools than for public schools.
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