1. Measuring Quality Improvement
Brandon Bennett

2. What are we trying to accomplish?
Distinguishing types of variation, performance and the use of targets
Idea of cascading measures
Revisiting our team level dashboards
Measurement for PDSA cycles

3. Two considerations on using data
What is the process/system currently doing?
Two more considerations:
Common Causes
Special Causes
What performance would we like?
Targets
Specifications
Aims imposed, hoped for, improved towards
Inspected out
Compare here
Remove/return to common cause
Institute improvement to achieve
Once here, intend special cause variation through change to move toward the specification of interest

4. But Why? Two Dangers for Leadership
Tampering – intervening/taking action on the process/system when performance is statistically stable – wastes resources and can make things worse
Failing to Intervene – when the process/system is indicating a need for correction/improvement, this failure can waste resources through poor management and/or lead to a more expensive fix further in the future

5. O1 P1 O2 P2 B S3 S2 S1 System of Feedback Measure Types
O = Outcome Measure
P = Process Measure
B = Balance Measure
S = Process Step Measure
PDSA = Learning Cycle Measure O2 P2 B S3 S2 S1
System of Feedback
PDSA1
PDSA2
PDSA3
PDSA4
© Improvement Science Consulting

6. O – Patient Satisfaction B
O - Mortality
P - ALOS
Measure Types
O = Outcome Measure
P = Process Measure
B = Balance Measure
S = Process Step Measure
PDSA = Learning Cycle Measure
O – Patient Satisfaction B P1 P2
S – Time to Theatre S2 S1
System of Feedback (Hip Fracture)
PDSA1
PDSA2
PDSA3
PDSA4 S3
© Improvement Science Consulting

7. Break Out Exercise Review your team level dashboard
Are you aimed too high? With too much emphasis on the outcome or process measures of interest?
If so, what are the steps in your process (Process Map)
What Process Step Measures could be developed to help you understand performance closer to the frontline of care?
Do you collect that information currently? How could you collect and use that information at the frontline?
i.e. CAM tool used reliably on all patients (CAM tooled used/All Admissions to ward 4 reported daily/weekly on a run/control chart)

9. As the scale of the test increases we move from qualitative to quantitative evidence
Very small scale test of a change idea
Large scale test of change idea or Implementation of a change idea
Evidence primarily Qualitative
Evidence primarily Quantitative with noticeable impact on process measures
Sequence of learning and change
© Improvement Science Consulting

10. Break Out Exercise
Revisit one Change Idea you have for improving care in your process area
See if you can develop measures that will help you learn about the Change Idea’s operational efficacy (increase degree of belief) starting with a test of change focused at the smallest PDSA level (i.e. 1 patient, 1 nurse, 1 day) and moving through 2 or three steps to the Process Step Measure Level
Note: The learning questions and individual PDSA measures should evolve with each cycle, if nothing else than to reflect the increased scale of the cycle

11. Break Out Exercise
Revisit the Process Step Measures you identified earlier
How would your team collect the information identified?
What would a data collection tool look like for these measures?
Where and how would you display the information collected for your team?

12. Model for Improvement Act Plan Study Do What are we trying to
accomplish?
How will we know that a change
is an improvement?
What change can we make that will result in improvement?
Model for Improvement
Act
Plan
Study Do
Langley, et al.