Finally, our findings showed that technical and scale efficiencies of all groups were improved at the end of the 5-year period although these were difficult years of the financial crisis. At this point, it is interesting to examine these results against the ordinary indicators used by hospital managers and policy makers. As can be seen in Table 1 for instance, the indicators of average length of stay and occupancy rate have been improved (-18.8% and +6.8% respectively). The same applies to the indicators for medical and other staff resources per inpatient case which were increased by 55% and 47% respectively. Going one step further, we examined all nine possible indicators that can be formed by the ratios of the three outputs when combined with the three inputs (i.e. the six variables that were used in DEA model). Simple comparisons of year’s 2013 values, against those of 2009, showed that eight out of nine indicators significantly improved, the only exception being the (meaningless) ratio of outpatient visits per bed, which was reduced by 10%. Thus, it can be argued that the findings of the study are in line with the whole “macro-picture” depicted in Table 1. The fact that the efficiency improvement between 2009 and 2013, as measured by DEA, is not of the extent implied by the large increment of ordinary indicators can be mainly attributed to its inherent characteristic of relativity in comparisons. The method is capable to perform only relative measurements of efficiency which as such are valid only inside the "borders" of the particular sample. For instance, the improved performance that would be expected by a plain +5% increment throughout all units' outputs, while keeping all their inputs constant, would not be captured by DEA. On the other hand, the overall augmented DEA scores in year 2013, compared with the ones five years before, indicate that eventually some inefficient hospitals in 2009 managed to operate closer to 2013’s efficient frontier defined by their counterpart efficient ones regardless of the relative possible shift and final distance between the two borders which cannot be accounted for by the method. It is evident therefore that DEA findings are complementary to the ones that can (and should) be derived by other means of performance evaluation.