Benoît Roland

Operating Theatre Optimization : A Resource-Constrained Based Solving Approach

The operating theatre is considered as the bottleneck of the hospital and as one of the most resources consuming unit. Therefore its management is of primary interest: an efficient planning allows to use as better as possible the availability of the operating theatre and reduce human and financial working costs. This paper deals with operating theatre planning optimization. We present a mathematical model combining surgeries planning and scheduling over short time horizon, and by taking into account renewable and nonrenewable resources availabilities. This model gets its inspiration from project management and especially resource-constrained project scheduling problem (RCPSP). We also introduce a genetic algorithm approach to heuristically solve the problem. We base our approach on the multi-mode variation of the RCPSP to define the related crossover, mutation and selection operators allowing the global search to work effectively

Assessing the impact of stochasticity for operating theater sizing

Over the last few decades, rational health care management and, in particular, operating theater planning, has attracted increased attention from practitioners and from the scientific community. However, although the operating theater environment is clearly stochastic, the impact of this randomness has often been ignored. In practice, simple rules based largely on past experience (such as keeping a safety margin), are most frequently used when making plans for the operating theater. In this paper, we propose an approach to help rationalize, at a strategic decision-making level, the way in which stochasticity can be taken into account in operating theater management, to help in the sizing and in the allocation of capacity. The three main sources of randomness are considered: durations of operations, unexpected emergencies and blocking because of a full recovery unit. Based on the Markov theory, our tool enables several performance measures to be estimated. An operating theater manager can use our approach to make informed decisions and assess, for example, the disruption of the planning by emergencies, the waiting times for emergency patients, the impact of the recovery unit, or the distribution of the working time. In particular, our approach helps determine the number of operations that should be planned in order to keep expected overtime limited. The tool is described in detail, discussed, and applied to the illustrative case of a Belgian hospital.

How stochasticity and emergencies disrupt the surgical schedule

In health care system, the operating theatre is recognized as having an important role, notably in terms of generated income and cost. Its management, and in particular its scheduling, is thus a critical activity, and has been the sub ject of many studies. However, the stochasticity of the operating theatre environment is rarely considered while it has considerable effect on the actual working of a surgical unit. In practice, the planners keep a safety margin, let’s say 15% of the capacity, in order to absorb the effect of unpredictable events. However, this safety margin is most often chosen sub jectively, from experience. In this paper, our goal is to rationalize this process. We want to give insights to managers in order to deal with the stochasticity of their environment, at a tactical–strategic decision level. For this, we propose an analytical approach that takes account of the stochastic operating times as well as the disruptions caused by emergency arrivals. From our model, various performance measures can be computed: the emergency disruption rate, the waiting time for an emergency, the distribution of the working time, the probability of overtime, the average overtime, etc. In particular, our tool is able to tell how many operations can be scheduled per day in order to keep the overtime limited.

Étude de la perturbation par les urgences du planning opératoire

Etant à la fois centre de dépense et source de revenus, le quartier opératoire fait l’objet d’une attention particulière au sein de la gestion hospitalière. Dans cet article, nous étudions le caractère stochastique de cet environnement qui, bien que négligé dans la littérature, est important en pratique. Nous considérons la perturbation engendrée par les urgences, ainsi que les durées aléatoires des opérations planifiées ou urgentes. Notre modèle, basé sur la théorie markovienne, permet de mesurer l’impact des aléas sur le planning des opérations, afin notamment de réserver des plages destinées à l’absorption des aléas et d’évaluer l’opportunité de dédier des salles aux urgences.