A New Insight in Medical Resources Scheduling of Physical Examination with Adaptive Collaboration

Medical resources of physical examination (P.E.) are often insufficient. The gap between providers and demanders are always existing and becoming more and more sensitive in some densely populated areas. If resources of P.E. departments are regarded as nodes, then each path selected by patients will constitute a small world network. Furthermore, with respect to traditional research concentrating on the feature between nodes in network, adaptive collaboration (AC) is in fact an important method to improve the group performance of the whole system in the small world network. Based on these, this paper deals with this kind of problem with respect to the scenario of P.E., which attempts to help decision makers of the health center to schedule limited resources and improve a patient's satisfaction and the system performance. It firstly abstracts a medical examination by Role-Based Collaboration (RBC) and its general model E-CARGO. The adaptive collaboration model is constructed by system states and optimized via series of group role assignments (GRAs), which is a subtask of RBC, and it can be accomplished by linear programming. All the proposed methods are verified by simulation experiments, and the team performance is improved via adaptation of the assignment strategies, which provides a new insight into the small world study.