Working Paper of Public Health Volume 2012 - Azienda Ospedaliera ...

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Azienda Ospedaliera Nazionale“SS. Antonio e Biagio e Cesare Arrigo”Working Paper of Public Healthnr. 16/2012Title: The performance of Italian hospitals and their hierarchical structure of administrativeemployees.Authors: Falavigna G. 1 , Ippoliti R. 2 , Manello A. 3 ;Type: Original articleKeywords: Hospital efficiency; Directional Distance Function (DDF); Hierarchicalorganization; Healthcare managementAbstractObject: considering the Italian health-care system, the present study analyzes what mightaffect the efficiency of hospitals.Methodology: in this work, authors propose the Directional Distance Function (DDF) toanalyze hospitals’ performance, considering efficient each medical center whichis able to maximize the production of medical treatments (good output) whilecomplying, at the same time, with budget constraints (i.e. minimizing theexpected bad output: financial loss).1 CNR-CERIS;Via Real Collegio, 3010024 Moncalieri (TO), ItalyTel.: +39.011.6824941, Fax: +39.011.6824966e-mail: g.falavigna@ceris.cnr.it2 Hospital “SS. Antonio e Biagio e Cesare Arrigo”Structure of Scientific PromotionVia Venezia, 1615121 Alessandria (AL), Italye-mail: rippoliti@ospedale.al.it3 CNR-CERIS and CNR-ISSMVia Real Collegio, 3010024 Moncalieri (TO), ItalyTel.: +39.011.6824946, Fax: +39.011.6824966e-mail: a.manello@ceris.cnr.it1
Azienda Ospedaliera Nazionale“SS. Antonio e Biagio e Cesare Arrigo”Working Paper of Public Healthnr. 16/2012Results: the empirical analysis suggests that an excessive allocation of employees at thehighest level of the hierarchical pyramid can affect the hospitals’ performance.Conclusions: a redistribution of employees among hierarchical levels is necessary to increasethe hospital’s efficiency.1. Introduction and theoretical backgroundConsidering the Italian healthcare system, the present study analyzes the aspects that mightaffect the efficiency of Italian hospitals. Even if this paper presents an application to theItalian case, the methodology to compute efficiency is well known in environmental field butits application in healthcare industry is very recent – as shown afterwards – and the resultscould be useful in terms of healthcare management. Indeed, in this work the authors analyzewhat might affect a specific definition of efficiency, which is calculated maximizing thehealthcare production but minimizing the potential financial loss. In other words, this workconsiders efficient each hospital which is able to maximize the production of medicaltreatments while complying at the same time, with budget constraints. Considering thecurrent era of austerity and the redefinition of the European welfare systems, as well therelated national spending review, this work is even more interesting and necessary. Indeed,even if this work is focusing on Italy, the policy implications could be extended to otherEuropean countries, which are facing the same spending reviews and the redefinition of theirnational welfare systems.In the last decades the frontier methodology has been widely adopted to compute theefficiency of healthcare management (Gattoufi et al., 2004). In particular, many authors havefocused on distinguishing between non-parametric and parametric measures in order to definethe best methodology to apply to the healthcare field (Hollingsworth et al., 1999;Hollingsworth, 2003). Parametric techniques, such as the regression model, assume a specificfunctional form in defining the frontier and they are susceptible to model misspecification,whereas non-parametric approaches are not (Rosko, 1999). Moreover, another significantpoint about frontier methodology, i.e., Data Envelopment Analysis (DEA) or StochasticFrontier Analysis (SFA), concerns the distinction between deterministic and stochasticapproaches. The former do not contain a random error component and then they can besensitive to outliers; the latter can separate inefficiency from random effect (Banker, 1993).Nevertheless, the problem linked to the impact of extreme observations on the frontier can be2
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