From the 2018 HVPAA National Conference
Susan Harvey (Johns Hopkins University), Lisa Mullen (Johns Hopkins Department of Radiology), Tali Amir (University of Pennsylvania)
Patient satisfaction and department efficiency are central pillars in defining quality in medicine. We describe a novel method for decision-making to improve efficiency, thereby decreasing wait times and adding value.
Objective: To determine if new technologies to assess workflow applied with supply chain logistics and simulation testing can optimize patient wait times, efficiency and “right size” levels of staffing and equipment.
Methods: We implemented a real-time location system (RTLS) in our academic breast-imaging department to study workflow, measure patient wait time, quantify equipment utilization, and identify bottlenecks. Then, using simulation tools employing supply chain algorithms, we modeled solutions with changes in staffing and equipment.
Results: 999 patient encounters were tracked over a 10-week period. Mean patient wait time was 27 minutes. The digital breast tomosynthesis (DBT) unit had the highest utilization rate and was identified as a bottleneck. Close to a 20% reduction in patient length of stay could be achieved by the replacement of a full field digital mammogram (FFDM) unit with a DBT unit and the addition of both a mammography technologist and a technologist dual trained in mammography and ultrasound.
Conclusion: Through a novel integration of RTLS with supply chain logistics and simulation testing, we were able to create a data driven model by which to accurately view our workflow. Thus, providing the data to inform decisions aimed at improved patient wait times, efficiency and workflow patterns.
Implications for the Patient
This quality improvement initiative has important implications, potentially allowing data driven decisions for staff hiring, equipment purchases and department layout. Further, patient wait times could be improved by these informed workflow and staffing solutions.