Analysis of operating room allocations to optimize scheduling of specialty rotations for anesthesia trainees.
BACKGROUND
Because specialty workloads and corresponding operating room (OR) allocations vary among days of the week, anesthesia residents and student nurse anesthetists are sometimes assigned to cases off rotation (e.g., scheduled for cardiac surgery but assigned to urology for the day). We describe a method to create hybrid rotations of two specialties (e.g., cardiac and vascular surgery), thereby reducing the numbers of days that trainees are "pulled" from their scheduled rotations.


METHODS
Raw data were the number of hours of OR time used by each surgical specialty on each workday for the preceding 9 months. These OR workloads were converted to the number of ORs to be allocated to each specialty for each day of the week on the basis of maximization of the efficiency of use of OR time. We considered all potential hybrid rotations of pairwise combinations of specialties to which trainees could be assigned. Integer linear programming was used to calculate the maximum number of trainees who could be scheduled to hybrid rotations and receive daily assignments matching those rotations.


RESULTS
Validity of the results was shown by using data from a small facility for which the optimal solution could be discerned by inspection. Validity (appropriateness) of the constraints was demonstrated by the exclusion of each constraint, resulting in answers that are obviously incorrect. Novelty and usefulness of the method was evidenced by its choosing from among hundreds of thousands of potential combinations of specialties and its identifying appropriate assignments that were substantively different from current rotations.


CONCLUSIONS
We developed a methodology to determine rotations consisting of combinations of specialties to be paired for purposes of trainee scheduling to reduce the incidence of daily assignments off rotation. Practically, with this method, anesthesia residents and student nurse anesthetists can be assigned cases within their scheduled rotations as often as possible.
Dexter
Franklin
F
Operations Research, Department of Anesthesia, University of Iowa, Iowa City, IA 52242, USA. Franklin-Dexter@UIowa.ed
Wachtel
Ruth E
RE
Epstein
Richard H
RH
Ledolter
Johannes
J
Todd
Michael M
MM
D000776:Anesthesiology / Q000193:education*; D001071:Appointments and Schedules; D003198:Computer Simulation; D004503:Education, Medical, Graduate; D017598:Efficiency, Organizational; D006801:Humans; D007396:Internship and Residency / Q000458:organization & administration; D017146:Models, Organizational; D009716:Numerical Analysis, Computer-Assisted; D009719:Nurse Anesthetists / Q000193:education* / Q000458:organization & administration; D009870:Operating Room Information Systems / Q000458:organization & administration*; D009873:Operating Rooms / Q000458:organization & administration*; D010561:Personnel Staffing and Scheduling / Q000458:organization & administration*; D010562:Personnel Staffing and Scheduling Information Systems / Q000458:organization & administration*; D015203:Reproducibility of Results; D013043:Specialties, Surgical / Q000193:education* / Q000458:organization & administration; D013997:Time Factors; D016526:Workload