The second step of the analytical framework is to examine size effects on hospital efficiency by determining the efficiency distribution of large and small hospitals. From DEA perspective, all hospitals in the sample are assumed to have the same production technology and thus face the same best-practice frontier. In fact, there is the possibility that large and small hospitals may practice different production technologies due to, for example, different operating environments. In this case, large and small hospitals may have their own separate frontiers that are different. To allow for this possibility, an investigation of frontier difference is introduced similar to the work of Grosskopf and Valdmanis (1987). This possibility is illustrated in Fig. 3. Suppose that Hospitals C, D, and E are all small hospitals and ysys represents its own separate frontier. Hospitals A and B are all large hospitals and the pooled frontier is represented by ypyp. Efficiency of Hospital C equals to OCV/OC and OCW/OC when measured relative to the separate and pooled frontiers respectively. The difference between separate and pooled frontiers is the distance between the two frontiers OC/OCV. This relative distance thus equals the ratio of the efficiency of C relative to the pooled frontier to the separate frontier (OC/OC)/(OCV/OC). The ratio captures the difference in the frontiers of large and small hospitals and it approaches unity when the difference between the two frontiers diminishes.