Abstract

ABSTRACTThis article presents a new model for constructing annual block schedules for family medicine residents based on the rules and procedures followed by the Family Medicine Department at the University of Texas Health Science Center in San Antonio (UTHSC-SA). Such residency programs provide 3 years of specialty training for recent medical school graduates. At the beginning of each academic year, each trainee is given an annual block schedule that indicates his or her monthly assignments. These assignments are called rotations and include a variety of experiences, such as pediatric ambulatory care, the emergency room, and inpatient surgery. An important requirement associated with a subset of the rotations is that the residents spend multiple half-day sessions a week in a primary care clinic treating patients from the community. This is a key consideration when constructing the annual block schedules. In particular, one of the primary goals of most residencies is to ensure that the number of residents in clinic each day is approximately the same, so that the number of patients that can be seen each day is also the same. Uniformity provides for a more efficient use of supervisory and staff resources. The difficulty in achieving this goal is that not all rotations allow for clinic duty and that the number of patients that can be seen by a resident each session depends on his or her year of training. When constructing annual block schedules, two high-level sets of variables are available to the program coordinator. The first is the assignment of residents to rotations for each of the 12 blocks, and the second is the (partial) ability to adjust the days on which a resident has clinic duty during each rotation. In approaching the problem, our aim was to redesign the current rotations while giving all residents a 12-month schedule that concurrently (i) balances the number of patients that can be seen in the clinic during each half-day session and (ii) minimizes the number of adjustments necessary to achieve the first objective. The problem was formulated as a mixed-integer program; however, it proved too difficult to solve exactly. As an alternative, several optimization-based heuristics were developed that yielded good feasible solutions. The model and computations are illustrated with data provided by the Family Medicine Department at UTHSC-SA for a typical academic year.

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