Because results of pathogen identification are often lacking when antibiotic therapy is initiated, treatment must frequently be instituted on an empirical basis. The type of empirical therapy will depend on the anticipated pathogen spectrum and naturally also on the prevailing resistance patterns. Inadequate antibiotic therapy may not only be associated with increased overall treatment costs, but will also have adverse effects on mortality. The clinician is frequently faced with an overabundant variety of microbiological data and may fail to interpret them correctly. Therefore, the present study has attempted to “translate” the available microbiological resistance data, frequently presented in the form of percentage rates, into concrete patient numbers and thus illustrate the frequency of inadequate antibiotic therapy. For this purpose, “Indication Failure” (IF), “Cumulative Indication Failure” (CIF) and “Balanced Indication Failure” (BIF) have been calculated based on available microbiological data.