DECISION SUPPORT SYSTEM FOR PREVENTING NO-SHOW TO MEDICALAPPOINTMENTS

The failure of customers to attend booked appointments, known as no-show, is a problem faced by companies worldwide, operating in medical assistance and transportation businesses. This work focused on the former, more particularly, on the medical appointments made via call-center. This paper presents a decision support system based on data mining for identifying, at booking time, the medical appointments with high risk of no-show, for helping online re-scheduling. Preprocessing and data transformation yielded embedding expert's knowledge and behavioral information. The a priori algorithm explicited the knowledge contained on the data and an MLP neural network estimated the risk of no-show. The system has been developed on a data set of 30,000 and tested on other 10,000 appointments from a healthcare company operating in Brazil. Both the risk estimation and the rules extracted attained high quality in the metrics defined and were considered very relevant by the company's specialist.