OBJECTIVES: In Germany,the financing mechanism aggravates the cost issue of so called high-utilizers. So far, there were no care management concepts as the mostly multimorbid, complex medical conditions were judged as individual, non-influenceable cases. We developed a method to reveal issues in treatment and care of this special insurance population to increase efficiency. METHODS: The most critical challenge for insurance companies lies in the identification of relevant insured, in order to specifically target the high effort of control and management. In this project we analyzed the secondary data of the members of a German insurance company in the course of four years. Based on this we first differentiated high-utilizers from average-utilizers. In the following we deflected by which means existing care management concepts could be complemented. Based on the longterm data observation we developed a prognostic model to predict future high-utilizers. RESULTS: High-utilizers were defined as the 5 % most expensive insurance-members, who generated 50% of total spending. We distinguished high-utilizers who caused the main costs in one specific care sector (pharmaceuticals and hospital) and patients who caused costs in multiple sectors (transsectoral). In addition, ultra high-utilizers were considered separately due to their extreme cost provocation. While it is possible to manage the first two groups by a combination or extension of existing cost reduction measures and care approaches such as disease management programs, ultra high-utilizers should be addressed by an individual and specifically developed case management. CONCLUSIONS: This segment of insured demands a stringent, integrated approach in order to efficiently employ the available financial resources. This study aims to explain a practical system for the controlling and management of expenses caused by high-utilizers based on our conclusion that the early identification and the specific management of high-utilizers in health care holds high financial potential and targeted programs are promising for care optimization.