1. QUALITY
MEASUREMENTS
Calle Lindén
Emily Moore
The Dinh Thi
2012

2. What we are measuring
 Readmission rate
 Patient
 75-85 years
 Heart failure, NYHA Class II-IV
 Slightly decrease of memory and understanding
 Knowledge -> Self-care -> Reduced risk for
readmission
 Intervention
 Telephone support and discharge education

3. Related to PDSA cycle
• Make a new PDSA • Quality issuses among
cycle according to patients with heart
the data we failure. What do we need
receive from to know about our
measurments patients and also which
theories. How can we
improve the situation
ACT PLAN
Study DO
• Descire our • Improve the self-
measured results care through
discharge
education and
telephone follow
up togheter with
web-based
services

4. Readmission rate
Author, year Outcome 1 Outcome 2
Koelling, Johnson, Cody Fewer days in hospital Reduced risk of
& Aaronson, 2005 readmission
Krumholz, Amatruda, Reduced risk of Fewer days in hospital
Smith, Mattera, readmission
Roumanis, Radford,
Crombie & Vaccarino,
2002
Kwok, Lee, Woo, Lee & Reduced risk of
Griffith, 2008 readmission
Domingues, Clausell , Reduced number of
Aliti, Dominguez & visits to the emergency
Rabelo, 2011 room

5. Why
 Measurable
 To measure if the intervention gives effect
 Patient
education and telephone support to
promote self-care
 Compare to other interventions
 Compare to other hospitals or other healthcare
facilities
 SMART goal

6. How
 Measure our variables
 Readmission rate/x patients
 Number of times those patients return to hospital
 Using statistical methods to measure
 Ratio scale
 Vizualize the measurements
 Line chart

7. How
 Count each time a patient in the study
achieves one of the possibilities
 Using statistical tools like the chi-square to see
if the the outcome is significant
Effect Intervention Control g Reductio (P-value and or
g n CI)
Possiblity 1 x (n) y (n) % value
Possiblity 2
Possiblity 3
Possiblity 4
Possibilty 5

8. Example of measure
 Patients who readmission to the ward
 n=100, 50 in each group
Effect Intervention g Control g Reduction
No readmission 20 10 -50%
One or more 10 20 +50%
readmission
Two or more 10 10 -
readmission
Readmission but 5 5 -
because of something
else
Died 5 5 -

9. Visualize with a line chart
 Add time as a variable
 Knowledge is temporary (Koelling, et al., 2005).
 Useful to measure variables over time
Readmission rate
a/b
Y-Values
Linear (Y-Values)
Time

10. Referenece
 Koelling, T., Johnson, M., Cody, R., Aaronson, K. (2005). Discharge
education improves clinical outcomes in patients with chronic heart failure.
Journal of the American association, 18, 179-185.
 Krumholz, H., Amatruda, J., Smith, G., Mattera, J., Roumanis, S., Radford,
M. et al. (2002). Randomized Trial of an Education and Support
Interventions to prevent Readmission of Patients With Heart Failure.
Journal of the American College of Cardiology, 39, 83-89.
 Kwok, T., Lee, J., Woo, J., Lee, D., Griffith, S. (2008). A randomized
controlled trial of a community nurse-supported hospital discharge
programme in older patients with chronic heart failure. The author journal
compilation, 17, 109-117
 Domingues, F., Clausell, N., Aliti, G., Dominguez, D., Rabelo, E. (2011).
Education and Telephone Monitoring by Nurse of Patients with Heart
Failure: Randomized Clinical Trial. ArqBrasCardiol, 96, 233-239.
 Hughes, R. Tools and Strategies for Quality Improvement and Patient
Safety. Patient Safety and Quality: An Evidence-Based Handbook for
Nurses: Vol. 3