Overscheduling

From Guide to YKHC Medical Practices

Definition: to schedule in excess of capacity.

Purpose: to achieve the desired productivity when a substantial percentage of patients are expected to be no-shows (i.e. not show up for their appointment).

For different no-show rates and different numbers of appointments, the likelihood of a certain number of patients showing up can be probabilistically modeled.

Second-order approximation (bootstrap method, 10,000 days)
Assumptions:

  1. Each patient has the same likelihood to no-show.
  1. The likelihood that each patient is a no-show is statistically independent of the likelihood of no-show of the other patients.


In the table below, the columns show increasing no-show rates (10% thru 60%) and the rows show increasing numbers of patients scheduled (6 thru 12).


10% 20% 30% 40% 50% 60%
6
Overscheduling 06 10.pdf Overscheduling 06 20.pdf Overscheduling 06 30.pdf Overscheduling 06 40.pdf Overscheduling 06 50.pdf Overscheduling 06 60.pdf
7 Overscheduling 07 10.pdf Overscheduling 07 20.pdf Overscheduling 07 30.pdf Overscheduling 07 40.pdf Overscheduling 07 50.pdf Overscheduling 07 60.pdf
8 Overscheduling 08 10.pdf Overscheduling 08 20.pdf Overscheduling 08 30.pdf Overscheduling 08 40.pdf Overscheduling 08 50.pdf Overscheduling 08 60.pdf
9 Overscheduling 09 10.pdf Overscheduling 09 20.pdf Overscheduling 09 30.pdf Overscheduling 09 40.pdf Overscheduling 09 50.pdf Overscheduling 09 60.pdf
10 Overscheduling 10 10.pdf Overscheduling 10 20.pdf Overscheduling 10 30.pdf Overscheduling 10 40.pdf Overscheduling 10 50.pdf Overscheduling 10 60.pdf
11 Overscheduling 11 10.pdf Overscheduling 11 20.pdf Overscheduling 11 30.pdf Overscheduling 11 40.pdf Overscheduling 11 50.pdf Overscheduling 11 60.pdf
12 Overscheduling 12 10.pdf Overscheduling 12 20.pdf Overscheduling 12 30.pdf Overscheduling 12 40.pdf Overscheduling 12 50.pdf Overscheduling 12 60.pdf



Limitations

  1. In reality, the patient no-show probability is only partially statistically independent but also partially statistically linked (i.e. via the weather).