I used the data that I’d previous posted on how to create a process map and pumped in the numbers about waiting in the doctors office. The mean time of a process is the average of how long it took to complete a single task (e.g. the average exam was 12 minutes) and the standard deviation was the amount of variation in the time (for the math majors out there it’s a normal distribution). So the average exam by a doctor took 12 +/- 6 minutes. I then plugged the following numbers into the simulator:

Registration 3 +/- 2 minutes

Medical History Review with Nurse 11 +/- 5 minutes

Consultation with Doctor 12 +/- 6 minutes

Check Out (book next appt) 7 +/- 3 minutes

The front desk completed the first and last tasks and the bottle neck is the doctor.

The results showed that the doctor was utilized 100% of the time with the front desk and nurse being idle about 50% of the time and 30 patients could be seen in two 3.5 hour sessions (7 hour day).

If the average time each task took was decreased by 20% then you could see 13% more patients

If the average variation (standard deviation) was decreased by 20% then you could see 7% more patients.

If you decreased both average and standard deviation then you could see 20% more patients.

The variation only accounts for 1/3rd of the ability to see more patients and the average time is closer to 2/3rds. The end result is I have to eat my words that variation is more important than mean when calculating office wait times.

*But if you’re looking to improve a process it goes to show that decreasing the variation in the time a process takes is [almost] as important as decrease the average time it takes.*
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