Distributed planning over time and people: balancing sampling effort and information accuracy

Coordination of dynamic schedules in complex environments requires the sampling of current status of the system. In many such systems, the information is unavailable or unreliable. Optimal sampling theory focuses on monitoring current situation for changes, with limited consideration of future changes or missing information. Models of sampling for coordination and scheduling must consider resolving missing or ambiguous data points. Human behavior involving this type of sampling balances the need for specific information with the effort required to attain the information. The effort exerted is inversely proportional to the projected uncertainty of the information obtained. Furthermore, informational uncertainty is mitigated through a process of collaborative "grounding and correction." This paper uses the coordination of Operating-Room Suite activities to demonstrate these factors, and discusses communication strategies within the operating room context.