The Common Sense Guide to Improving Palliative Care > 2.4 Measuring Your Success
Now you need to work on the critical question: How will we know that our change is an improvement? In our example, How will we know when cancer patients have their pain level lower than their pain goal by the end of their second hospital day? The simplest answer is by measuring your progress.
All improvement requires change, but not all changes lead to improvement.
Working on your measurement plan often teaches you a lot about your aim; at that point, go back and restate the aim so that the aim and measure match (and also end up reflecting what you and your team really want to do).
How do we decide what to measure? The answer lies in our aim statement: implicit in the aim is the way to measure your success.
To choose a measurement strategy, we suggest the following.
Let us use the previous example to identify a measurement strategy. Remember the aim:
Aim Statement: In 30 days, 90% of inpatient cancer patients on unit 4A will report pain levels lower than their own pain goal by the evening shift of their second hospital day.
One measure to chart the progress of this aim statement is the percentage of all cancer patients on unit 4A who have pain levels lower than their stated pain goal by the evening shift of the second hospital day. In this example, the numerator is the number of patients with pain who meet their pain goal, and the denominator is all cancer patients with pain on admission. Try to link your measurement strategy to your aim. Make it practical and important. Each chapter in this book provides suggestions about measurement strategies that work. There are three types of measures: outcomes, process, and adverse effects.
An outcome measure seeks an accurate means of assessing directly what you care about most, such as the patient/family experience.
Using our pain example, an outcome measure is the percentage of all cancer patients with pain on unit 4A who have pain levels lower than their stated pain goals by the evening shift of the second hospital day. (Levels are based on a scale of 0–10.)
To calculate this measure, you need to know how many cancer patients had pain on admission and stayed until the evening of their second hospital day; of these, you must record how many had pain below their own target by the evening shift of their second hospital day. A cancer patient who has no pain on admission would not be included in the denominator. Notice that this way of specifying the measure would miss postoperative pain on the third hospital day and also patients who died or went home in a day. Like most measurement strategies, you have to pick a specific measure that best relates to your aim. Working on your measure often requires that you go back and sharpen your aim.
A process measure assesses how your care delivery system is working. Do certain desirable actions happen in the right order and at the right time?
Using our pain example, some process measures would be as follows.
Improved pain management in cancer patients requires looking at the steps in the process to identify, treat, and reassess pain in the patients on unit 4A. Are patients being assessed for pain when they are admitted to the unit, and, once assessed, are they being treated? Once treated, are they being reassessed? These process measures are important and often are easier to determine than outcome measures, partly because they happen more often. The major concern with relying only on process measures is whether they are tightly linked to the outcome you really care about. Often, team members will measure processes just long enough to be sure that they are working correctly, but they will keep measuring outcomes until they achieve the aim.
Changes that you make in the patterns of care often result in adverse effects. For example, having nurses spend time doing pain assessment, treatment, and reassessment on unit 4A may result in longer waiting times for patients in the emergency room to move to unit 4A. You need to monitor likely or important side effects while keeping surveillance on the project's overall effects.