Purpose: Long wait times are a primary source of dissatisfaction among patients enrolled in early-phase clinical trials. We hypothesized that an automated patient check-in system with readily available display for increasing awareness of waiting intervals would improve patient flow and use of our rooms, with decreased turnover time and increased throughput.
Methods: We recorded in-room wait times for patients seen in our clinic and observed the logistics involved in the blood collection process to delineate causes for delays. We then implemented a three-step strategy to alleviate the causes of these delays: (1) changing the collection of materials and the review of faxed orders, (2) improving our LabTracker automated database system that included wait time calculators and real-time information regarding patient status, and (3) streamlining lower complexity appointments.
Results: After our intervention, we observed a 19% decrease in mean wait times and a 30% decrease in wait times among patients waiting the longest (95th percentile). We also observed an increase in staff productivity during this process. Modifications in LabTracker provided the biggest reduction in mean wait times (17%).
Conclusion: We observed a significant decrease in mean wait times after implementing our intervention. This decrease led to increased staff productivity and cost savings. Once wait times became a measurable metric, we were able to identify causes for delays and improve our operations, which can be performed in any patient care facility.
Copyright © 2016 by American Society of Clinical Oncology.