Predicting future staffing needs at teaching hospitals: use of an analytical program with multiple variables

Area of Science:

• Healthcare Management
• Surgical Operations
• Medical Education

Background:

• Teaching hospitals face evolving staffing needs due to resident work hour regulations and service demands.
• Accurate staffing models are crucial for maintaining operational efficiency and educational quality.

Purpose of the Study:

• To develop and utilize a predictive model for future staffing requirements in a hospital surgery service.
• To analyze the financial and educational impacts of various staffing scenarios.

Main Methods:

• A computer model was constructed incorporating variables such as staff distribution, salaries, work hours, educational value, patient volume, and efficiency.
• The model projected outcomes including staff hiring needs, expenses, and educational impact over a 5-year period.

Main Results:

• Reducing resident duty hours to 60/week requires hiring 10 physician assistants, costing over $1.1 million, or hospitalists at a higher cost.
• Implementing protected academic time increases costs by $568,000.
• A 10% efficiency gain can reduce expenses by 21%, while 2% annual growth increases costs by over $700,000.

Conclusions:

• Replacing residents with alternative providers incurs significant financial and human capital costs.
• Efficiency improvements offer potential cost mitigation, suggesting a need for paradigm shifts in teaching hospital care delivery to meet educational mandates.