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In health care organizations, management of both human and material resources implies decision making. When seemingly equivalent strategies are possible, simulation can help to make a decision on better grounds. The SHARE workframe was designed to address the specificities of health care and to provide a comprehensive environment for modelling and simulating health care processes. The typology of objects is defined as Actors, subdivided in Clients and Resources and Elementary Operations. Graphical tools allow us to build processes from these objects and to create their relationships. Various strategies based on either clinical or managerial changes may be investigated. After a simulation, graphical tools allow us to display summary information on the utilization of all actors, waiting times, and goodness of execution. The use of SHARE is exemplified with the analysis and simulation of changes in the Pulmonary Function Testing Laboratory of the Saint-Antoine Hospital, Paris.

This paper describes the "SHARE" workframe, designed to provide a comprehensive environment for modeling and simulating health care processes. The objects defined within SHARE are Actors, subdivided in Clients and Resources, and Elementary Operations. Graphical tools allow to build processes from these objects, and to specify their relationships. Various strategies based on either clinical or managerial changes may be investigated. Summary information on the utilization of all actors, on waiting times and goodness of execution may be displayed after a simulation. Better description of processes, and their study a priori will improve reliability, quality of care and satisfaction of patients.

XNBC is a software package for simulating biological neural networks. Two neuron models are available, a leaky integrator model and an ion-conductance model. Inputs to the simulated neurons can be provided by experimental data stored in files, allowing the creation of 'hybrid' networks. Graphic tools are used to describe the modeled neurons as well as the network. Neuron and network parameters can be modified during the simulation, to mimic electrical stimulations and drugs action. The temporal evolution of the network and of selected neurons can be visualized. A point process, frequency or dynamic analysis of the simulator output can be performed. The successive stages of the creation of a hybrid network are explained.