Impact of IMPACT: Longitudinal Analysis of an Integrated Participant Scheduling System in a Clinical Research Setting

Abstract

Rapidly increasing costs have been a major threat to our clinical research enterprise. Improvement in appointment scheduling is a crucial means to boost efficiency and save cost in clinical research and has been well studied in the outpatient setting. This study reviews nearly 5 years of usage data of an integrated scheduling system implemented at Columbia University/New York Presbyterian (CUIMC/NYP) called IMPACT and provides original insights into the challenges faced by a clinical research facility. Briefly, the IMPACT data shows that high rates of room and resource changes correlate with rescheduled appointments and that rescheduled visits are more likely to be attended than non-rescheduled visits. We highlight the differing roles of schedulers, coordinators, and investigators, and propose a highly accurate predictive model of participant no-shows in a research setting. This study sheds light on ways to reduce overall cost and improve the care we offer to clinical research participants.

Figure 1.. Sample screenshot of the IMPACT scheduling tool for Schedulers (left side) and Coordinators (right side)

Figure 2.. Visit status flow outlining temporary status (yellow) and final status (green). Visit count in each status also included.

Figure 3.. Logistic Regression (left). Wide and Deep Model (middle). MLP Classifier (right).

Figure 4.. Visit count by status each quarter

Figure 5.. Sunburst plot of visit status (total visit count = 71,788).

Figure 6.. Flow rate for each clinical research visit room