Methodologies to improve patient flow
Inpatient and Ancillary Services
University of Southern California
Patient flow is improved with analytical techniques and process change eliminating hospital bottlenecks. Radiology, surgery, bed management, and a colonoscopy clinic are improved. Simulation, integer programming, queuing models, and process redesign significantly increase throughput and bed utilization. We learned how to apply such techniques for successful and meaningful change.
We discuss analytical methods and process improvement techniques for patient flow. Using these techniques, we targeted bottlenecks at the large Los Angeles County General Hospital. Challenges included data availability, organizational support, and selecting appropriate methods. Three years of work yielded meaningful insights. Four subprojects resulted in findings and implemented changes.
The CT department required reduced patient queuing. We developed a computer simulation model that was robust enough to handle the variation in the number of machines and technician staffing. The results and process redesign helped radiology double its throughput.
A finite-horizon integer-programming model optimally allocated surgery time blocks to clinical specialties while minimizing length of stay. A number of patient priorities and clinical constraints were included. The optimization model was input to a simulation model to determine expected patient flow.
For bed management, utilization and shorter inpatient bed turnaround was the objective. Data analysis of patient charts provided insights by statistical analysis. Using these results, administrators were able to reduce waiting in ER and shorten the turnaround of beds.
The GI clinic was experiencing a large backlog and increased capacity was required to meet the community's needs for colonoscopy procedures. Data analysis and a simulation model created opportunities for improvement.