Metaschedulers can distribute parts of a Bag-of-Tasks (BoT) application among various resource providers in order to speed up its execution. The expected completion time of the user application is then calculated based on the run time estimates of all applications running and waiting for resources. However, due to inaccurate run time estimates, initial schedules are not those that provide users with the earliest completion time. These estimates increase the time distance between the first and last tasks of a BoT application, which increases average user response time, especially in multi-provider environments. This paper proposes a coordinated rescheduling algorithm to handle inaccurate run time estimates when executing BoT applications in multi-provider environments. The coordinated rescheduling defines which tasks can have start time updated based on the expected completion time of the entire BoT application. We have also evaluated the impact of system-generated run time estimates to schedule BoT applications on multiple providers. We performed experiments using simulations and a real distributed platform, Grid'5000. From our experiments, we obtained reductions of up to 5% and 10% for response time and slowdown metrics respectively by using coordinated rescheduling over a traditional rescheduling solution. Moreover, coordinated rescheduling requires little modification of existing scheduling systems. System-generated predictions, on the other hand, are more complex to be deployed and may not reduce response times as much as when using coordinated rescheduling.