Cardiothoracic surgery planning involves different resources such as operating theatre time, beds, IC beds and nursing staff. In the daily practice of the Thorax Centre case study setting, the planning focuses on optimal use of operating theatre time, though the performance of the Thorax Centre as a whole is often more limited by other resources. For operating theatres a master surgical schedule is used to allocate operating theatre resources at tactical level for a longer period. Operational schedules at weekly level are derived from this master schedule. Within cardiothoracic surgery different categories of patients can be distinguished based on their requirement of resources. The mix of patients operated is, therefore, an important decision variable for the Thorax Centre to manage the use of these resources. In this paper we will consider the planning problem at the tactical level to generate a master surgical schedule that realises a given target of patient throughput and optimises an objective function for the utilisation of resources. The problem can be mathematically approached by mixed integer linear programming, which we already demonstrated in a previous paper. The specific topic of the current paper is to investigate the influence of using a stochastic instead of a deterministic length of stay. We will discuss the new mathematical model developed for this planning problem. The results obtained by the model indicate that we can generate master surgical schedules with a better performance on target utilization levels of resources by considering the stochastic length of stay.
analysis was to develop two cost effectiveness models taking into account the new management of the treatment of AF and VTE in France. The clinical and cost benefits of VKA (with/without the use of a PAS) has been evaluated versus new oral anticoagulants (NOAC): dabigatran, rivaroxaban and apixaban. Methods: A Markov model was built for the treatment of AF and a decision tree for the treatment and prevention of VTE. In the VKA arms, both models integrate the possibility to adjust the percentage of time spent by patients within INR therapeutic range. In the VTE model, outcomes were expressed in cost per avoided event whereas in the AF model in cost per QALY. Results: In both models, apixaban is the strategy producing the least thromboembolic and hemorrhagic events whereas AVK strategies are the cheapest treatments (2 to 2.5 times less than NOAC treatments). The use of the software for the treatment and prevention of VTE allows to save € 3,192 per avoided event and for the AF treatment € 7,557 per extra QALY gained and € 6,688 per avoided event. ConClusions: Based on French guidelines for economic evaluation, apixaban and VKA + PAS are efficient strategies in AF.
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