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A Patient Panel Assignment Strategy to Balance Provider Workload in Family Medicine
Yu-Li Huang1, David R Rushlow2
1Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN 55905, USA.
A new patient panel assignment framework effectively balances provider workload in primary care by predicting appointment needs. This strategy significantly reduces workload variations, though some patient reassignments are necessary for optimal distribution.
Area of Science:
- Primary Care Management
- Health Services Research
Background:
- Provider workload and burnout are critical issues in primary care, often driven by patient panel size and mix.
- Effective patient panel assignment is essential for balancing provider workload and preventing burnout.
Purpose of the Study:
- To develop and demonstrate a patient panel assignment framework for equitable workload distribution among primary care providers.
- To improve the balance of appointment volume across providers in a family medicine setting.
Main Methods:
- Developed a framework predicting patient appointment needs using patient characteristics and Adjusted Clinical Group (ACG) scores.
- Grouped patients by predicted appointment needs and determined provider group caps.
- Allocated patients to providers within established caps to ensure even distribution.
Main Results:
- The proposed framework significantly reduced appointment variations among providers, with an 85% decrease in standard deviation and 84% in range for a group of 14 providers.
- Demonstrated improved workload balance through 100 simulated reassignments.
- 11.7% of patients required reassignment to achieve balanced workloads.
Conclusions:
- The developed framework is effective in supporting provider workload balance in primary care.
- Future research should focus on minimizing patient reassignments while maintaining care continuity and incorporating additional workload factors.
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