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Azienda Ospedaliera Nazionale“SS. Antonio e Biagio e Cesare Arrigo”Working Paper of Public Healthnr. 16/2012Taking Italian regions into account, table 2 presents descriptive statistics of efficiency scores,which have been obtained from the data proposed in the previous table and adopting theabove-mentioned methodology.According to this methodology, we can rank the various Italian regions. The most efficientone is Marche, in which two hospitals have a score equal to zero; whereas the worst regionsare Sicily and Campania. However, there are only three hospitals with anomalous scores:A.O. “G. Rummo” and A.O. “S.G. Moscati” (Campania), and A.O. “Gravina e S. Pietro” ofCaltagirone (Sicily), which will be dropped in the second stage.Moreover, note that some Italian regions (i.e. Valle d’Aosta, Abruzzi and Molise) and theautonomous provinces of Trento and Bolzano have been dropped since there are noobservations. In other words, the regional healthcare systems of these observations are shapedaround medical centers linked to the Local Health Authorities.Table 2Efficiency scores, Italian regions (2007), weak disposability assumptionRegion Mean Std. Dev. Freq.Basilicata 4 0.009187 0.012992 2Calabria 4 1.000000 0.000000 2Campania 4 5.174808 9.774207 10Emilia Romagna 2 0.016396 0.036663 5Friuli Venetia Giulia 2 0.195734 0.046389 3Lazio 3 0.358458 0.327520 5Liguria 1 0.077128 0.118245 3Lombardy 1 0.149334 0.168133 29Marche 3 0.000000 0.000000 2Piedmont 1 0.222437 0.309571 8Puglia 4 0.206719 0.292345 2Sardinia 5 1.000000 0.000000 2Sicily 5 259.266710 931.193880 13Tuscany 3 0.203307 0.169660 4Umbria 3 0.000000 0.000000 2Veneto 2 0.052052 0.040912 2total 36.557101 346.329860 941 North-west; 2 North-east; 3 Center; 4 South; 5 Islands;According to the classification of the Italian National Institute of Statistics (ISTAT), table 3proposes the same descriptive statistics but in aggregate version, considering 5 geographicalmacro-areas (i.e. North-west, North-east, Center, South, and Islands).Table 3 indicates the most efficient Italian macro-area (i.e. North-east), as well as the worstone (i.e. South of Italy), but without considering the above-mentioned anomalous values. In4 The choice of this specific year is affected by data availability. Indeed, data about technical inputs are currentlyproposed only for that year.9
Azienda Ospedaliera Nazionale“SS. Antonio e Biagio e Cesare Arrigo”Working Paper of Public Healthnr. 16/2012other words, the three anomalous observations are not considered in this table (A.O. “G.Rummo”, A.O. “S.G. Moscati”, and A.O. “Gravina e S. Pietro”).Table 3Efficiency scores, Italian macro areas (2007), weak disposability assumptionMacro area Mean Std. Dev. Freq.Islands 1.00000 0.00000 14South 0.74513 0.42951 14Center 0.20042 0.25836 13North-east 0.07733 0.09022 10North-west 0.15854 0.19906 40total 0.37530 0.41313 91In the second stage, the authors try to explain what might affect hospital inefficiency byperforming an empirical analysis, i.e. a regression analysis of efficiency scores (dependentvariable) for some key explanatory variables (independent variables). Table 4 shows theseexplanatory variables but considering only inefficient hospitals, i.e. efficiency scores higherthan zero (24 hospitals are efficient and they do not appear in the second stage).Table 4Descriptive statistics of explanatory variablesVariable Obs. Mean Std. Dev. Min MaxEntropy Index 67 2.22895 0.16284 1.38000 2.4200North-west 67 0.43284 0.49921 0.00000 1.0000North-east 67 0.08955 0.28769 0.00000 1.0000Center 67 0.08955 0.28769 0.00000 1.0000South 67 0.17910 0.38633 0.00000 1.0000Islands 67 0.20896 0.40963 0.00000 1.0000Administrative employees (number) 67 262.05970 170.76240 9.00000 798.0000People in charge Index 67 1.50799 1.85756 0.33448 13.6477D Index 67 1.00052 0.50030 0.00000 2.5333C Index 67 0.87938 0.27142 0.22533 1.5796B Index 67 1.02991 0.51600 0.04255 2.2127A Index 67 2.04245 2.65957 0.00000 12.8596* If a log transformation is appliedSource: Italian national healthcare systemThe Entropy Index represents the level of specialization of the medical centers. Taking thesupply of medical treatments into account, this variable should normalize the consideredsample. Moreover, according to the classification suggested in the previous tables, fivedummy variables are adopted to capture the effect of the geographical macro-areas.According to the current bibliography on management (Simon, 1947), the administrativestructure of an institution should be shaped around a hierarchical pyramid with few people incharge at the top and many workers with lower skills at the bottom. As for Italy and its public10
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