The administrative staff of the HCP wanted to use analytics to predict whether or not a patient would show up to a scheduled appointment for several of their clinics. By identifying patients that are most likely to not show up to their appointment, the staff can quickly fill these open slots. Doing so would help the hospital serve more people at a quicker pace.
Care had to be taken to validate model outcomes and make sure not to overbook a time slot.
Pinnacle Solutions used predictive analytics to help the HCP make informed decisions when scheduling patients. Models were built off historical data in order to identify patients that are not likely to show up to an appointment. These models score new data on a daily basis and allow staff to find opportunities to see more patients.
A powerful end-to-end SAS solution was implemented: 1) SAS Office Analytics was used to prepare the historical data for modeling and score new data based on the predictive models, 2) SAS Enterprise Miner was used to build, modify and validate complex predictive models that produced accurate results, and 3) SAS Visual Analytics provided the mechanism to automatically load scored data into memory servers and populate informative dashboard reports via a web browser.
The administrative staff is able to review the reports while scheduling patients, as well as track the overall performance of the models.