Purpose: This study’s purpose was to optimize the efficiency of and to design a scalable research scheduling team to meet the growing demands of an academic cancer center with increasing clinical trial accruals. Methods: The Plan, Do, Study, Act improvement methodology was deployed to increase the efficiency of research scheduling, to reduce non–value-added (NVA) activities, and to reduce cycle time to meet takt time. In the Plan phase, voice-of-the-customer interviews were conducted. In the Do phase, the baseline workflow was mapped and billing data were analyzed. In the Study phase, cycle time, takt time, and capacity analysis metrics were calculated at baseline. In the Act phase, interventions were implemented to increase efficiency by reducing NVA activities and increasing value-added activities, and metrics were reassessed after intervention. Results: An 8% increase in appointment requests was noted from baseline to after intervention, and the cycle time for appointment scheduling decreased by 11%, demonstrating increased efficiency. Process steps decreased from 15 to 10, eliminating NVA activities and rework and waiting, two types of waste. Conclusion: Although efficiency increased, the number of total appointments scheduled weekly increased by 4%, resulting in a reduced takt time, or a shorter time to schedule each appointment to meet demand. A capacity analysis demonstrated that even after interventions, an additional 0.5 full-time employee is required to reduce cycle time to equal takt time. Capacity analysis creates a scalable framework for the scheduling team and facilitates movement from reactive to proactive staffing, which can be applied throughout the research enterprise.
Contributions on Clinical Decision Support from the 2018 Literature
