1. INTRODUCTION. In university hospitals, choices are made to which extend specialized health care will be supported. It is characteristic, for this type of care, that it takes place in a process of the continual advance of medical technology and the growing awareness by consumers and payors. Specialized healthcare contributes to the hospital qualifiers having a political and strategic impact. The hospital board needs information for planning and budgeting these new tasks. Much of the information will be based on data stored in the Hospital Information System (HIS). Due to load limitations, instant retrieval is not preferred. A separate executive information system, uploaded with HIS data, features statistics, on a corporate level, with the power to drill-down to detailed levels. However, the ability to supply information on new types of healthcare is limited since most of these topics require a flexible system for new dedicated cross-sections, like medical treatment from several specialisms and functional levels. 2. DATA RETRIEVAL AND DISTRIBUTION. During the information analysis, details were gathered on the necessary working procedures and the administrative organization, including the data registration in the HIS. In the next phase, all relevant data was organized in a relational datamodel. For each topic of care, dedicated views were developed at both low and high aggregation levels. It revealed that a matching change of the administrative organization was required, with an emphasis on financial registration aspects. For the selection of relevant data, a bottom-up approach was applied, which was based on the registrations starting from the patient administrative subsystem, through several transactional systems, ending at the general ledger in the HIS. Data on all levels was gathered, resulting in medical details presented in quantities, up to financial figures expressed in amounts of money. This procedure distinguishes from the predefined top-down techniques generally used for management and executive information systems. Data was regularly collected from the HIS, then converted and reorganized into relational datasets using XBase protocols. After having performed central quality controls and privacy protection measures, the datasets were distributed electronically to local PCs. Standard low-cost software packages enable analyses by user-friendly selection and presentation facilities. 3. EVALUATION. The method developed for data retrieval is flexible and easy to implement. If all basic data is registered in the HIS, the procedure can be applied for all strategic hospital functions that require planning and controlling during a certain time. Critical success factors and pitfalls will be presented in the poster. Using one consistent dataset, the information required about production and budget is presented at several functional levels and is quantified in units familiar to that level. The motivation for fast and accurate registration in the HIS was improved from the moment the medical and administrative staff recognized their own data in the feed-back on specialized health care.