Optimize Recommendation Engine for Marketing System in Healthcare CRM

Healthcare marketing is one of the most interesting research domains due to the high complexity and legal regulations of the medical data on the one side and the large volume of data required by marketing processes on the other side. Current research proposes a solution of adapting a commonly used marketing process, recommendation to healthcare industry needs to healthcare industry. Optimization of the standard recommendation processes have been identified as the main point of adaptation due to the high volume of data available in healthcare systems along with the need of analyzing the complete set of available data. Caching results represents one of the most common optimization techniques used in software implementation and due to highly sensitivity of medical data appears to be non-applicable. This paper is making use of segmentation of data sets combining patient profiles in target groups that are to be passed to recommendation scenarios as input data allowing catching results for healthcare recommendation scenarios.