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What is the effect of variability in demand on your waiting lists ?

Demand is never stable. It is always variable. And the (amount of) variability of demand has an effect on the waiting lists.

(a waiting list is a group of patients waiting to be served = to receive the care needed)

To dive into this question I will start with an example:

In the PFM Hospital the Radiology department is suffering from long waiting lists for an MRI-scan. For non-urgent examinations the waiting list is 10 weeks.

The hospital wants to reduce the waiting list and has agreed with the Radiologists and Radiology staff to increase the opening hours until the waiting list is below 4 weeks.

A short analysis shows that demand is on average 100 patients per week, and the department performs on average 100 examinations per week.

This analysis strengthens the department in their opinion that increasing the opening hours will reduce the waiting list.

 

 

Will the proposed intervention solve the problem of the long waiting list ? Also in the long term ?

Before answering this question we will play a dice game.

We need 2 players, each with a dice. One player is ‘demand’, the other player is ‘MRI-capacity’.

We play 4 rounds with 20 dice throws in each round. Each dice throw represents one week of demand IN, and MRI-capacity provided. So, if player 1 (demand) throws 4, then demand for MRI-capacity is 4, if player 2 throws in the same round 3, then MRI-capacity is 3, and the result is that 1 patient is placed on the waiting list.

The MRI-capacity in the 4 rounds is changed. In round 1 player 2 is allowed to add 3 to the dice roll. For example if player 2 has thrown 2, then he can add 3 to that roll, so the total available MRI-capacity is 5.

In round 2, player 2 adds 2 to the dice roll, in round 3, one is added to the roll, and in round 4, nothing is added to the roll.

What we simulate here is a situation with different amounts of overcapacity in MRI-capacity. In round 1 the overcapacity is 3 (average dice roll is 3,5 + 3 = 6,5). In round 4 the average demand is equal to capacity (both 3,5).

What happens with the waiting lists ?

I have played this small games several time, and each time the results are similar.

Here an example of the results:

In round 1 the waiting lists are low, in round 4 the waiting lists are high. In round 1 we have a high amount of overcapacity (86% more capacity than demand –> 6,5 versus 3,5).

In round 4 demand is on average equal to capacity (both 3,5). So, in the situation of equal demand and capacity we have a high increase of waiting lists. The reason, of course, is variability in dice rolls.

We can also simulate this game several times with different conditions:

(example taken from the tool ‘Patient Flow Manager™’ )

The red scenario indicates a scenario with a high overcapacity (just like in round 1). The green scenario indicates a scenario with on average equal demand and capacity (round 4). This results in a long waiting list. The blue scenario indicates a scenario with equal demand and capacity (both on average 3,5), but in this scenario the variability of MRI-capacity is low, because the dice rolls are restricted to 3 and 4. We see that the waiting lists still increase, but less fast as in the red scenario.

So if, based on the games played, we have to answer the question: Will the proposed intervention solve the problem of the long waiting list ? Also in the long term ?

What would you answer ? See below the ‘To think about…’ questions to sharpen your thinking about the examples given.

Playing the above-mentioned game, or making simulations is very powerful to sharpen the thinking of the people you work with. Try it!

To think about…

In this series we don’t just provide answers. We try to trigger your thinking by posing questions that you have to answer…

So, let’s start…

  • What is the reason of the increase in waiting lists ? Is it variability in demand ? Is it variability in capacity ? Is it a shortage in capacity ? Or a combination ?
  • What will be the long term effect of the proposed intervention in the example in this article ?
  • How much extra capacity would be needed to keep the waiting list low ? (see also one of my previous articles ‘How much extra bed capacity do need ?’ –> this can also be related to waiting lists. I will cover this in one of the future articles.
  • Do you have a good view on variability of demand in your hospital ?
  • Do you take into account variability in demand when defining the necessary capacity ?
  • Do you play games to sharpen the thinking of your people ?

Do you know about Patient Flow Management ? tries to trigger people’s thinking and learning by posing a series of questions (sometimes simple questions, sometimes complex questions) about the dynamics of Patient Flow Management/Hospital-Wide Capacity Management. The questions are based on real-life examples as I encounter them in hospitals. In case you have further questions, or are in need of more in-depth information, then please contact me at gwen.roosemont@ximius.eu.

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