Regular measurement is essential to determine if changes actually improve outcomes. Teams should select measures of outcomes, processes, and balancing factors to assess the impact of changes. Run charts displayed over time help teams observe patterns and determine if improvements are real and sustained by showing the effect of changes on measured factors. Teams should collect useful, simple, minimal, and real-time data to speed improvement without slowing the process down.

1. Measurement for Improvement
All improvement involves change, but not all
change is an improvement. So, how will we
know that a change is an improvement?
Only through measurement can teams
determine whether a change actually made
things better. Regular and frequent tracking of
results establishes a momentum that
encourages early engagement and active
participation in the process of delivering rapid
and sustainable improvements. Regular tracking
is a powerful tool for assessing progress and
benchmarking against others.
Initially you might find some resistance to data tracking. Data collection can be perceived
as a threat. There are two types of measurement data: data to improve and data to
judge. Data to judge is based on the question Who? Data to improve, on the other hand,
is based on the questions Why? How? What? Quality improvement uses data to
improve the system, not judge. If people feel measurement may be used against
them, they may not participate fully or they may present inaccurate data.
In order to assess the impact of your changes, select at least one measure from each of
the family of measures: outcome, process, and balancing measures.
Outcome Measures
Outcome measures answer the question: what is better for the patient? These
measures are typically amenable to counting and can often be measured using a
standard tool. Outcome measures directly measure what is better or worse for the
patient or client. Examples of outcome measures include: incidence of pressure ulcers,
scores on a risk scale, number of infections, patient wait times.
Process Measures
Process measures answer the question: what is better about the way care is
delivered? These measures indicate whether the processes of care have improved.
Examples of process measures include: how often clinical guidelines are followed,
number of doctors writing orders for prophylaxis, number of staff using proper hand
washing technique between patients. Process measures should focus on areas of care
that, if improved, are known to improve patient outcomes. Improvements in processes
of evidence-based care will eventually lead to improvements in patient or client
outcomes. For example if you focus on consistently re-positioning patients at risk of
developing a pressure ulcer (a care process) according to evidence-based guidelines,
then you will reduce incidence of pressure ulcers (an outcome).

2. Balancing Measures
Balancing measures answer the question: what in the system may be adversely
affected by the changes? We cannot change one part of a system without influencing
other parts in some way. Balancing measures help teams track the impact of their
changes on other parts of the system, including unintended consequences. For
example, if we start to regularly re-position patients at risk of developing a pressure-
ulcer, we will want to monitor the impact of our intervention on patients (e.g., sleep, pain)
and staff (e.g., workload, injuries).
Measures should be:
• Useful – they needn’t be perfect – measures should tell you whether the changes
are having the desired impact
• Simple – use existing sources of data whenever possible; any new measures should
be easily incorporated into day-to-day work
• Minimal – collect just enough data to satisfy the needs of the team; measurement
should speed improvement, not slow it down
• Real-time – routinely collect and present data to gauge progress and the continuing
impact of the change
Measurement can be a powerful tool for stimulating and sustaining improvements.
Run Charts
Improvement takes place over time. Determining if
improvement has really happened and if it is lasting
requires observing patterns over a certain period. Run
charts are graphs of data over time and are one of the
single most important tools in performance
improvement.
Using run charts has a variety of benefits:
• They help improvement teams formulate aims
by depicting how well (or poorly) a process is
performing.
• They help in determining when changes are truly
improvements by displaying a pattern of data
that you can observe as you make changes.
• They give direction as you work on improvement
and information about the value of particular
changes.
Copyright © 2004 Institute for Healthcare Improvement
www.ihi.org

3. Your Data and Run Charts
Once you have determined what data you will be collecting, when you will be collecting
it, who is collecting it and who is recording/entering the data, a spreadsheet in Excel
can be used to store this information. Data should be entered chronologically and only
one set of data per run chart.
In graphing your data, the X-axis is the time and the Y-axis represents the value of the
measurement being monitored (often graphed in percentage form).
Microsoft Excel is a program that will allow you to create tables and graph your data.
If you are not familiar with using Excel to create run charts, the pen and paper method
can be used in creating your run charts. Be sure your data is collected in a table format,
on paper, in Word, or entered onto a spreadsheet in Excel.
Directions have been included for the creating of run charts using:
• The Pen and Paper Method
• Microsoft Excel
(Note: Microsoft Excel is one of the many programs available that can be used for the creation of
run charts).
Run Charts: The Pen and Paper Method
1. Draw the X-axis and Y-axis as shown on the right: Title…….
a. X-axis data represent time
b. Y-axis data represent the measurement
2. Label your axes. New staff
hired
y-axis
3. Chart the data using the appropriate scale, in the
sequence in which they occurred.
(measure)
Staff Educ.
4. Draw a line to connect the points on the graph.
5. Title the chart. x-axis (time)
6. Indicate where changes were initiated.
7. Repeat for each measurement.

4. Run Charts: Using Microsoft Excel
Once your data has been entered you are now ready to create your run chart. To
generate your run chart from the spreadsheet in Excel, go to the data table and proceed
as follows:
1. Left mouse-click on “Insert” in the toolbar
2. Choose the option “Chart”
3. “Chart Wizard Step 1”
4. Under the tab, “Standard Types”, choose “Line”. Then click “Next”.
5. “Chart Wizard Step 2”
• Choose the appropriate series “Row” or “Column” for your data
• If your data has been entered in a row (across the spreadsheet, choose “Row”)
• If your data has been entered in columns (down the spreadsheet, choose “Column”)
• Data range: choose the data set that you want to be charted. This can be done by
choosing the entire data set (click and drag). Then click “Next”.
6. “Chart Wizard Step 3”
• Under the tab “Titles”, enter the information for the following:
• Chart Title, X axis, Y axis
• Then, click “Next”
7. “Chart Wizard Step 4”
• This step determines where the chart will be placed. Choose the option to place the
chart in “as new sheet” to have the graph drawn on a separate sheet from the data
chart.
• Click on “Finish”
8. Repeat for each measurement.
A run chart created in Excel will look similar to the following:
Average ER wait times per month
120
100
A gw it tim s in )
e (m s
80
60
v a
40
20
0
1 2 3 4 5 6 7 8 9 10
Month

5. Additional information:
Institute for Healthcare Improvement. (2004). Process analysis tools: Run chart. Boston,
MA: Institute for Healthcare Improvement. Downloaded from
http://www.ihi.org/IHI/Topics/Improvement/ImprovementMethods/Tools/Run+Chart.htm
Neibauer, A. (1999). Office 2000 Made Easy. Berkely: Osborne McGraw-Hill.
Creating a graph in Excel; The Basics.
http://biology.dbs.umt.edu/biol101/labs/General/excelgraph.pdf