You have to understand,
who is going to be engaged in this activity and get
air coverage for them to collect data because they're doing other jobs at the same time.
You have to have your operational definition to create
a data collection tool to build a know how this data will be collected.
You might have to train folks.
And a lot of times what happens is if you have
more than one individual collecting that data,
what I recommend is you go out with them and
each individual person is witnessing and they're capturing
their own data and then you can compare to ensure that
you have that reproducibility going on there.
So, you want to basically want to have reproducibility
and be able to articulate how we did this and why.
Create spreadsheets.
So now that we have this data,
you have to have a way to collaborate together if you will.
You have to have a way to summarize it and make it meaningful.
So, you might need a spreadsheet to do that,
you might need to create a chart,
or something along those lines.
Key metric do's and don'ts.
Do, have others "weigh in".
You might have noticed this pattern already that,
every single do starts with have others "weigh in" on this.
Have your stakeholders "weigh in",
and see if it makes sense.
You have to ensure that the data needed is attainable.
If you can't get it it's not going to help you.
You have to ensure that the process relates to both the problem and goal.
You only have one problem,
one key element of a problem,
and one goal that relates to that problem.
Include both numerator/denominator to explain a percentage.
And identify that operational definition
we just talked about and data collection mechanism.
Some of the things I try to avoid are,
using action words like improve, reduce.
The metric is simply a metric, it's a measure.
So, there shouldn't be any verbs in there.
Choose something you can't measure or measure with accuracy.
So, a while back we had an issue with medications being unlabeled.
And we had a heck of a time understanding how we
were going to capture the rate of unlabels.
So, it's one of those things we had to put a lot of time,
energy, and effort into.
And we really weren't overly successful and understand the data.
Casting it in stone.
Don't think that once you establish that key metric,
it will be the key metric.
It's going to morph like the problem statement and go well over time.
Express in dollars, unless it's all about the money.
Focus on the clinical benefit and
possibly list the dollars as an added benefit in the end.