Utilizing Service Recovery to Identify Bottlenecks in the Treatment Planning Process and Provides Sustainable Improvement in Operational Workflows

Abstract

The Radiation Oncology treatment planning process necessitates many moving parts. Highly specialized teams work in concert with many aspects of planning, contingent on the completion of one item before the start of the next. A delay caused by unplanned barriers to completion can have significant impact on the final production time. Not all team members are aware of bottlenecks in the process. When bottlenecks occur, it is a fundamental practice to have a service recovery mechanism in place. Service recovery is the process of making things amenable for the patient after something in the process has gone erroneous with the healthcare experience. There is published data that indicates using a transparency dashboard provides benefits in time reduction in the treatment planning process. We contend that building a dashboard with service recovery identifiers could help improve overall time to start and further create a learning mechanism for teams to reduce barriers for a sustainable improvement.Using electronic patient information management system scripts and python language; we generated a dashboard with built in service recovery alerts before the failure occurs. Each step during the planning process were given three separate time labels. Standard streetlight colors with green indicating the activity are within the designed timeframe, yellow indicates that the due time is near, and red indicating the item has been delayed. Expected hours excluded hours before 8 am, after 5 pm, weekends, and holidays. Alert mechanisms were created to alert the yellow and red items to leaders who could act on determination of recovery mechanism. These mechanisms included a dashboard published on the local intranet that contained all patients and current stop light status and daily email updates of tasks that were in a yellow or red status.The results from this concerted effort were dramatic. From October 2019 to December 2020, we were able to reduce the time from CT SIM to start from 10.9 to 5.9 days, an astounding 46% reduction in overall time. The success can be attributed to significant reduction in yellow and red-light items. The total number of green lights demonstrated a 22% rise, 715 to 871. Yellow and red items were reduced by 41% (147 to 87) and 59% (298 to 123). More common bottlenecks included resident contours to MD approval; which demonstrated improvement in total time by 44% (2.7 to 1.5 days). Green light items were reduced by 28%, meanwhile reducing yellow and red-light items by 48 and 83% respectively. Dosimetry planning to MD Approved Plan demonstrated improvement total time of 44% (2.3 to 1.2 days). Green light items were reduced by 17%, meanwhile reduction in yellow and red by 41 and 88% respectively.A dashboard with built-in service recovery warnings proved to have sustained benefits in the treatment planning process. The treatment planning process benefited in identification of recurring bottlenecks in the treatment planning process which resulted sustained improvement throughout the 14-month process.