  The survey data sets are important sources of data and their successful
exploitation is of key importance for informed policy-decision making. We
present how a survey analysis approach initially developed for customer
satisfaction research in marketing can be adapted for the introduction of
clinical pharmacy services into hospital. We use two analytical approaches to
extract relevant managerial consequences. With OrdEval algorithm we first
evaluate the importance of competences for the users of clinical pharmacy and
extract their nature according to the users expectations. Next, we build a
model for predicting a successful introduction of clinical pharmacy to the
clinical departments. We the wards with the highest probability of successful
cooperation with a clinical pharmacist. We obtain useful managerially relevant
information from a relatively small sample of highly relevant respondents. We
show how the OrdEval algorithm exploits the information hidden in the ordering
of class and attribute values and their inherent correlation. Its output can be
effectively visualized and complemented with confidence intervals.
