We have presented a health-care decision support system, which has been used experimentally on a large database of clinical records, in order to show how data warehousing and data mining can effectively support evidence-based medicine. The proposed system enables medical guide lines identification by exploiting evidence based clinical history of a patient, standard protocols, and other patients histories. A user study has been presented to provide an early system validation focusing on usability aspects.
A broader validation focusing on the quality of the system provided information and the results of inferences is currently being accomplished. In particular, other than the medical data sources we had available, we also needed the active involvement of medical doctors to assist us in writing CD forms and scripts for specific medical domains, and to help us evaluate the quality of inference results. To this end, with the help of medical doctors from our medical school we are currently integrating data sources concerning a specific disease (Sepsis), for which we are also writing CD forms and scripts. This will also allow us to perform more sophisticated interpretations of textual information contained within medical records, for which we are also investigating the use of sketch recognition strategies, due the handwritten text abounding in legacy clinical records