An Innovative Interactive Modeling Tool to Analyze Scenario-Based Physician Workforce Supply and Demand

Area of Science:

• Health Workforce Analytics
• Medical Education Policy
• Computational Health Science

Background:

• Effective physician workforce management necessitates accurate assessment of current and future physician supply.
• This data is critical for informed decisions regarding graduate medical education funding.
• Existing methods may not adequately capture the complexities of evolving healthcare landscapes.

Purpose of the Study:

• To describe a dynamic modeling tool for measuring and forecasting physician supply and demand.
• To demonstrate the tool's applicability across medical specialties, using pathology as a specific example.
• To provide a framework for educators, policymakers, and specialty organizations to analyze workforce dynamics.

Main Methods:

• Development of a computer-based software model.
• Population of the model with survey data and expert estimates on current and emerging physician activities.
• Inclusion of diverse factors such as service types, practice settings, healthcare reform (Patient Protection and Affordable Care Act), technological advancements, demographic shifts (aging population), and new payment models (capitated, value-based, team-based care).

Main Results:

• The model quantifies how various factors influence the supply and demand for physician services.
• It identifies potential shifts in physician roles, required expertise, and practice efficiencies.
• The tool is adaptable for analyzing workforce needs in any medical specialty.

Conclusions:

• The dynamic modeling tool offers a robust method for physician workforce assessment and planning.
• It supports strategic decision-making for graduate medical education and healthcare policy.
• The model facilitates adaptation to evolving healthcare systems and payment models, ensuring physician readiness for future roles.