ABSTRACT INTRODUCTION: The development of patient classification systems (PCS) in fields other than acute medicine raises the question if the principle of using existing data (i.

e. diagnoses; procedures where available) is sufficent to describe the products of hospital care. METHODS/MATERIAL: The essence of a PCS (type “iso-cost”) is to estimate costs of treatment needed in a defined setting by means of a description of the patient status (conditions) and the treatment goals.

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Two hypotheses guided our research into PCS development: (1) The description of patient status and treatment goals has to include multiple aspects which ideally are coded by using scales to show changes during the course of time. (2) In a multiprofessional team, costs of treatment of each professional sector can depend on different aspects of the patient status. Therefore, in a first step treatment costs could be described multidimensionally: for each profession sector separately. – In a test study, 1795 treatment weeks of 274 patients of 4 medical rehabilitation institutions were described by a variety of patient status indicators.RESULT: The test study showed that the sum of nursing times per week and patient were best grouped by a two-dimensional grid constructed by using the motor scale and the cognitive scale of the Functional Independence Measure (FIM). These scales are used as indicators of the patient status.

The six final groups lead to a variance reduction of approx. 65%. But the time spent by several therapeutic professionals could not be explained by the same indicators.CONCLUSIONS: The test study encourages further research about the introduction of multidimensional and scaled measures in order to explain the multidimensional cost vectors of a multiprofessional health treatment. In the acute setting a first model could be to use DRGs to estimate costs related to or dependent on physicians’ activities and a measure of functional status to estimate (independent) nursing costs. A proposed research field is the treatment of patients with chronic diseases.