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A very busy orthopedic clinic in a university health system was experiencing long lines at check in. This was not only a patient disatisfier, but impacted patient through put by causing patients to be late to their appoints. A new pilot program was going to be implemented that was feared would make the problem even worse.
Our task was to help the department find a "no build" solution.
The first step was define the problem by documenting existing flow, processes, volumes, patient mix and timing. This was established a baseline model that virtually recreated the existing conditions.
Several scenarios were then proposed. These included the use of self check in for repeat patients, form fill out areas and minor tweaks to the appointment schedule. In the end it was demonstrated that the long lines could be dramatically reduced with a combination of the methods without changes to staff or the physical environment.
A very busy orthopedic clinic in a university health system was experiencing long lines at check in. This was not only a patient disatisfier, but impacted patient through put by causing patients to be late to their appoints. A new pilot program was going to be implemented that was feared would make the problem even worse.
Our task was to help the department find a "no build" solution.
The first step was define the problem by documenting existing flow, processes, volumes, patient mix and timing. This was established a baseline model that virtually recreated the existing conditions.
Several scenarios were then proposed. These included the use of self check in for repeat patients, form fill out areas and minor tweaks to the appointment schedule. In the end it was demonstrated that the long lines could be dramatically reduced with a combination of the methods without changes to staff or the physical environment.
Patient Arrival Schedule
Minor shifts have big impacts to queue.
Existing Conditions Model - Click to watch
Simulation of adjusted patient schedule- Click to watch