Maximizing clinical rotation placements for US medical students: exploring an optimization model.

Area of Science:

• Medical Education
• Operations Research
• Health Systems Management

Background:

• US medical schools traditionally rely on community clinicians for student training.
• Physician willingness to host medical students has declined.
• The COVID-19 pandemic has raised concerns about the adequacy of patient encounters for meaningful clinical experiences.

Purpose of the Study:

• To develop an optimal scheduling model for medical student clinical rotations.
• To maximize the number of patients medical students encounter during their rotations.
• To ensure equitable distribution of patient experiences among students.

Main Methods:

• A 16-week longitudinal clinical experience model was implemented.
• Medical students attended family medicine or internal medicine clinics twice weekly.
• A mixed integer linear programming model was used to optimize patient scheduling, maximizing minimum patient visits per learner.

Main Results:

• The optimization model determined a minimum of 87 patients (3 per day) per student over 16 weeks.
• The model increased the number of students assignable to a clinic from 1 to 8 per rotation.
• Pilot studies demonstrated the model's ability to allocate more students without reducing patient encounters.

Conclusions:

• The mixed integer linear program effectively assigns more students to high-visit clinics for optimal learning.
• The model achieves equitable rotation plans by maximizing the minimum number of patients per student.
• This approach allows for increased student allocation without compromising the quality or quantity of clinical experience.