Related Experiment Videos
Using simulation to improve the operational efficiency of a multi-disciplinary clinic
A G Kalton1, M R Singh, D A August
1University of Michigan, Ann Arbor, USA.
Journal of the Society for Health Systems
|January 1, 1997
Summary
Operational challenges at a multi-disciplinary breast care clinic were addressed using simulation. The study identified bottlenecks causing long waits and physician conference disruptions, offering insights for improved clinic management and patient flow.
Area of Science:
- Health Services Research
- Operations Management
- Clinical Practice Management
Background:
- Multi-disciplinary care in a single visit is a growing healthcare trend.
- The University of Michigan Breast Care Center, established in 1985, exemplifies this model.
- Increased patient volume and a shift in patient mix (more returning patients) created operational strains.
Purpose of the Study:
- To analyze operational inefficiencies within a busy multi-disciplinary breast care clinic.
- To identify the root causes of patient wait times and delays in care recommendations.
- To provide data-driven recommendations for improving clinic operations and patient flow.
Main Methods:
- A simulation study was conducted to model the clinic's patient flow and resource allocation.
- The simulation focused on identifying bottlenecks in clinical evaluation sessions and patient care conferences.
- Analysis aimed to understand the impact of increased patient load on operational efficiency.
Main Results:
- Physician participation in patient care conferences was compromised due to busy clinical schedules.
- Patients experienced prolonged wait times and delays in scheduling follow-up appointments.
- The study pinpointed specific areas of congestion within the clinic's operational workflow.
Conclusions:
- Simulation modeling offers valuable insights into managing complex multi-disciplinary clinics.
- Addressing identified bottlenecks is crucial for maintaining high-quality patient care and operational efficiency.
- Optimizing patient flow and resource allocation can alleviate strains caused by increased demand.