A Goal Programming Model for Fairly Scheduling Medicine Residents

In this study we develop a goal programming model for scheduling the shifts of the residents in a Qatari hospital. The residents are assigned for on-call shifts during their training (called first resident), as well as working during the regular day shifts (called helper). Residents schedules must address several considerations like work rules and hospital coverage requirements of two different departments: Oncology and Hematology as well as fairness of the workload distribution. The problem has been formulated using goal programming and solved using CPLEX. We were able to solve problems of realistic size to optimality in a few seconds

Development and implementation of a computer-aided method for planning resident shifts in a hospital

Ce mémoire propose une formulation pour le problème de confection d'horaire pour résidents, un problème peu étudiée dans la litérature. Les services hospitaliers mentionnés dans ce mémoire sont le service de pédiatrie du CHUL (Centre Hospitalier de l'Université Laval) et le service des urgences de l'Hôpital Enfant-Jésus à Québec. La contribution principale de ce mémoîre est la proposition d'un cadre d'analyse pour l’analyse de techniques manuelles utilisées dans des problèmes de confection d'horaires, souvent décrits comme des problèmes d'optimisation très complexes. Nous montrons qu'il est possible d'utiliser des techniques manuelles pour établir un ensemble réduit de contraintes sur lequel la recherche d’optimisation va se focaliser. Les techniques utilisées peuvent varier d’un horaire à l’autre et vont déterminer la qualité finale de l’horaire. La qualité d’un horaire est influencée par les choix qu’un planificateur fait dans l’utilisation de techniques spécifiques; cette technique reflète alors la perception du planificateur de la notion qualité de l’horaire. Le cadre d’analyse montre qu'un planificateur est capable de sélectionner un ensemble réduit de contraintes, lui permettant d’obtenir des horaires de très bonne qualité. Le fait que l'approche du planificateur est efficace devient clair lorsque ses horaires sont comparés aux solutions heuristiques. Pour ce faire, nous avons transposées les techniques manuelles en un algorithme afin de comparer les résultats avec les solutions manuelles. Mots clés: Confection d’horaires, Confection d’horaires pour résidents, Creation manuelle d’horaires, Heuristiques de confection d’horaires, Méthodes de recherche localeThis thesis provides a problem formulation for the resident scheduling problem, a problem on which very little research has been done. The hospital departments mentioned in this thesis are the paediatrics department of the CHUL (Centre Hospitalier de l’Université Laval) and the emergency department of the Hôpital Enfant-Jésus in Québec City. The main contribution of this thesis is the proposal of a framework for the analysis of manual techniques used in scheduling problems, often described as highly constrained optimisation problems. We show that it is possible to use manual scheduling techniques to establish a reduced set of constraints to focus the search on. The techniques used can differ from one schedule type to another and will determine the quality of the final solution. Since a scheduler manually makes the schedule, the techniques used reflect the scheduler’s notion of schedule quality. The framework shows that a scheduler is capable of selecting a reduced set of constraints, producing manual schedules that often are of very high quality. The fact that a scheduler’s approach is efficient becomes clear when his schedules are compared to heuristics solutions. We therefore translated the manual techniques into an algorithm so that the scheduler’s notion of schedule quality was used for the local search and show the results that were obtained. Key words: Timetable scheduling, Resident scheduling, Manual scheduling, Heuristic schedule generation, Local search method

Operating Room Scheduling in Teaching Hospitals

Operating room scheduling is an important operational problem in most hospitals. In this paper, a novel mixed integer programming (MIP) model is presented for minimizing Cmax and operating room idle times in hospitals. Using this model, we can determine the allocation of resources including operating rooms, surgeons, and assistant surgeons to surgeries, moreover the sequence of surgeries within operating rooms and the start time of them. The main features of the model will include the chronologic curriculum plan for training residents and the real-life constraints to be observed in teaching hospitals. The proposed model is evaluated against some real-life problems, by comparing the schedule obtained from the model and the one currently developed by the hospital staff. Numerical results indicate the efficiency of the proposed model compared to the real-life hospital scheduling, and the gap evaluations for the instances show that the results are generally satisfactory

New Methods for Resolving Conflicting Requests with Examples from Medical Residency Scheduling

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138246/1/poms12728.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138246/2/poms12728-sup-0001-SupInfo.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138246/3/poms12728_am.pd

Balancing Medical Resident Education and Workload while Ensuring Quality Patient Care

Medical residency is a requirement for medical professionals to practice medicine. Residency programs in internal medicine lasts 3 years and require residents to undergo a series of supervised rotations in elective, inpatient, and ambulatory units. Typically a team of chief residents develops a yearly rotational schedule that assigns residents to various departments for each week of the year, and for each day of the week. Scheduling resident rotations is complex as it needs to consider various academic, managerial, and legal restrictions while ensuring that the resulting schedules facilitate patient care and are balanced in terms of resident educational experience, workload, and resident satisfaction. This study proposes: (1) a multi-objective optimization approach for generating year-long resident rotation schedules; (2) an AHP (Analytical Hierarchy Process) model to compare schedules across multiple criteria and facilitate their adoption and implementation; (3) a methodology for studying the interaction between weekly and daily resident rotation schedules.; (4) an optimization based approach for ensuring continuity of care at outpatient clinics; and, (5) a methodology for evaluating resident assignment policies to outpatient clinics

A permutation flowshop model with time-lags and waiting time preferences of the patients

The permutation flowshop is a widely applied scheduling model. In many real-world applications of this model, a minimum and maximum time-lag must be considered between consecutive operations. We can apply this model to healthcare systems in which the minimum time-lag could be the transfer times, while the maximum time-lag could refer to the number of hours patients must wait. We have modeled a MILP and a constraint programming model and solved them using CPLEX to find exact solutions. Solution times for both methods are presented. We proposed two metaheuristic algorithms based on genetic algorithm and solved and compared them with each other. A sensitivity of analysis of how a change in minimum and maximum time-lags can impact waiting time and Cmax of the patients is performed. Results suggest that constraint programming is a more efficient method to find exact solutions and changes in the values of minimum and maximum time-lags can impact waiting times of the patients and Cmax significantly

Assigning patients to healthcare centers using dispatching rules

This study proposes a model for the balanced assignment of patients to healthcare centers in a region. In the suggested model, it is supposed that patients want to go to the nearest center, which causes an imbalance in the workloads of resources between centers. This disproportion is undesirable not only for the centers but also for the patients. Thus, balancing assignments is targeted. This goal is expressed in a model with a multi-objective function. Since balancing is one of the main goals of the sectorization concept, we characterize the model based on it. Unlike studies in the literature, we do sectorization employing dispatching rules. This diminishes the problem's complexity and makes it suitable for solving actual, large, and dynamic problems. We simulated the system using the Rockwell Arena software. We consider the effect of different seasons, days, and hours on the system. The dispatching rule used for sectorization is optimized using the OptQuest software. The numerical results demonstrate that by optimizing the dispatching rule, it is possible to enhance the objective function significantly.info:eu-repo/semantics/publishedVersio

Improving Physician Schedules by Leveraging Equalization: Cases from Hospitals in U.S.

In this paper, we consider physician scheduling problems originating from a medical staff scheduling service provider based in the United States. Creating a physician schedule is a complex task. An optimal schedule must balance a number of goals including adequately staffing required assignments for quality patient care, adhering to a unique set of rules that depend on hospital and medical specialties, and maintaining a work-life balance for physicians. We study various types of physician and hospital requirements with different priorities, including equalization constraints to ensure that each provider will receive approximately the same number of a specified shift over a given time period. A major challenge involves ensuring an equal distribution of workload among physicians, with the end goal of producing a schedule that will be perceived by physicians as fair while still meeting all other requirements for the group. As the number of such equalization constraints increases, the physician scheduling optimization problem becomes more complex and it requires more time to find an optimal schedule. We begin by constructing mathematical models to formulate the problem requirements, and then demonstrate the benefits of a polyhedral study on a relaxation of the physician scheduling problem that includes equalization constraints. A branch-and-cut algorithm using valid inequalities derived from the relaxation problem shows that the quality of the schedules with respect to the soft constraints is notably better. An example problem from a hospitalist department is discussed in detail, and improvements for other schedules representing different specialties are also presented