DFG Research Grants Project 405488489
Resident scheduling in teaching hospitals with the use of quantitative methods
This research project mainly deals with the strategic and tactical-operative scheduling of medical residents. In addition to relieving the medical staff who are currently responsible for the planning process, this research project increases the predictability of structured training. This gives hospitals the opportunity to increase the quality of their training and, consequently, their attractiveness to other hospitals. In addition, supervisors from different departments can better assess the knowledge of residents and thus to keep the level of service, which is particularly important in hospitals, permanently high even when changing residents.
Progress
21.08.2018: First Meeting
The research team of Prof. Dr. Jens O. Brunner and Prof. Dr. Manfred Blobner have a first meeting to identify organizational tasks before the project starts.
09.07.2018: Funding received
Prof. Dr. Jens O. Brunner and Prof. Dr. Manfred Blobner are informed by the DFG that their research grants project “Resident scheduling in teaching hospitals with the use of quantitative methods” will be funded.
Projects
Strategic task-related resident scheduling with uncertainty
Sebastian Kraul; Andreas Fügener; Jens O. Brunner; Manfred Blobner
In this project, we investigate the effects of uncertainty regarding interventions on the total number of residents that a hospital can employ without violating the program length.
We consider the training phase of physicians after finishing medical school. They specialize in a common field like ophthalmology or anesthesiology and are called residents. Technological progress in health care leads to increasing complexity in the requirements of physician training. As a consequence, those programs are often not only time-related but also task-related. Task-related means that residents should perform a given number of different interventions in their program. Typically, a resident will follow a rotation across different clinical departments, where the number of performed interventions per period may be estimated. Predicting the exact number of interventions is usually not possible. Accordingly, a resident might not be able to perform all of the required interventions during the planned rotation, resulting in an extension of the program. In this project, a new model is presented that calculates the number of residents a hospital can reliably train on a strategic level. Our model also provides the corresponding training schedule. It considers minimum requirements of both time-related stays in specific departments as well as task-related interventions that have to be performed. The robustness of the model can be set by management to handle uncertainties in interventions. A Dantzig-Wolfe decomposition is used to accelerate the solution process, and a new pattern generation approach that can construct multiple patterns out of one solution is developed. The termination of the column generation algorithm is accelerated significantly by this method. The model is evaluated using real-world data from a resident program for anesthesiology in a German university hospital. The results demonstrate that near-optimal solutions with an average optimality gap of below five percent can be achieved within computation times of few minutes.
Tactical task-related resident scheduling focusing on continuity of care
Sebastian Kraul
In this project, we investigate the impact of continuity of care and fair training progress for annual schedules.
This project presents a new model for constructing annual schedules for medical residents based on the regulations of a German teaching hospital as well as the program restrictions of the German Medical Association. Since resident programs of physicians do not only vary between disciplines but also between countries, it is essential to evaluate the main characteristics of the program. The main difference between the already well-studied resident programs in the US and the one of this project is the task-related structure. Residents need to perform different interventions several times to become specialists. This study will focus on Germany since there was a judgment in 2015 that hospital management needs training schedules guaranteeing the success of the resident program in time. Therefore, a new formulation of a tactical resident scheduling problem is presented. The problem is formulated in two stages considering the total number of interventions, equal progress in training as well as continuity of care. As the second stage of our formulation is a quadratic program and even by linearization standard solvers are not able to generate high-quality solutions within 24 hours, a genetic algorithm using standard crossovers is developed for the second stage constructing annual schedules for an existing stock of residents. We evaluate our algorithm by comparing the solutions of the genetic algorithm and standard software with a real-world situation of a German training hospital from 2016.
Publications
Coordination
Prof. Dr. Jens O. Brunner
Chair of Health Care Operations/Health Information Management, Faculty of Business and Economics, University of Augsburg – University Center for Health Sciences at the Augsburg Clinic – UNIKA-T, Neusässer Straße 47, Augsburg 86156, Germany
and
Prof. Dr. Manfred Blobner
Clincs for Anaesthesiology, Technical University of Munich, Klinikum rechts der Isar, Ismaninger Straße 22, Munich 81675, Germany