Control Charts in Health Care

This post is an edited version of a message I sent to the Deming Electronic Network.

I find the “control charts in health care” thread quite interesting.

From Mike Woolbert’s post [link broken, so I removed it]
> I have read many comments about the 8 minute ambulance trip.
> This doesn’t seem to be a system measure, but a result measure.

It seems to me the 8 minute (90% of the time) measure is an attempt at a process measure (in a sense, you can see it as a result measure, but it is also a measure that will have an impact on overall results and as such can be used a process indicator). For it to be a process measure rather than than a process target however, it should actual be a measure of what has happened not a statement that we want to have 90% arrive within 8 minutes.

Jonathan Siegel’s comments [link broken, so I removed it] on this topic were excellent.

The control chart was developed to aid in process improvement. A control chart helps monitor the process (to aid in putting in place counter-measures, when needed, and for identification of special causes). The control chart can be used to see if the process is in control and what the expected results from the system are.

The 90% in 8 minutes measure [link broken, so I removed it] seems to me to be the desire or goal (as a proxy for a “customer specification” or voice of the customer“). The control chart will show what the process is capable of: voice of the process. There could be another voice of the process that excludes the 10% longest times, but I don’t think that would be a control chart, it would be something else. I think that is fine, as long as what it was, and is not, is understood. Maybe there is some way to have the 90% measures as a control chart that I just don’t think of it right now.

Learning that the process is in control (using a control chart) can help guide the improvement efforts. When the process is in control certain process improvement strategies are likely to be effective. And PDSA pilots can be analyzed based on the knowledge that the system is in control. I think Brian Joiner’s 4th Generation Management has very good information on this topic, see pages 140-153. Essentially, focus on improving the process as a whole, using PDSA and experimentation, rather than focusing on special causes. In addition, those pages talk about stratifying and disaggregating the data to help focus improvement efforts.

If the system is not in control different improvement strategies are most likely to be effective. Again 4th Generation Management has good ideas pages 138-140. Essentially, in this case the type of management most often seen, find causes and react is often the best strategy. The long term strategy should be to bring the process into control and then improve the process.

Thinking about the ambulance response process I have the following thoughts.

It seems likely the 8 minute figure is based on experience such that the system outcomes (the health of the patient) will decline as times increase, which makes sense to me. And possibly the 8 minute figure is based on some studies that make that a sensible figure to use. But I would want to get the data (both looking at the literature overall and viewing internal records), on why 8 minutes versus 6 or 10.

Knowing how important the 8 minute target is may be critical to improvement strategies. The point of using a control chart, and many of the management improvement tools, are to improve the efficiency and effectiveness of resources spent improving. The trick is not really to improve (that is pretty easy) the trick is to improve quickly and effectively (and in a competitive marketplace to improve more quickly than competitors). Where improvement resources are targeted is critical. In deciding which improvement options to explore it is important to understand the impact on the outcome (in this case the health of the patient).

As stated in an earlier message, the real aim is improving the outcome for the patient. Assuming that outcomes decline as time increases. One way to do this is by finding and eliminating special causes (or adding them in case the special causes are beneficial).

I think the control chart would need to include all data not just 90%. The control chart is a measure of the performance of the process. The 90% within 8 minutes seems more

This message could benefit from more thought and editing on my part but I have to run so I will send it as it is and hope it is useful – even in this rough form.

John Hunter

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