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  • Hughes, R. Tools and Strategies for Quality Improvement and Patient Safety.Patient Safety and Quality: An Evidence-Based Handbook for Nurses: Vol. 3
  • Ecd0425

    1. 1. QUALITYMEASUREMENTS Calle Lindén Emily Moore The Dinh Thi 2012
    2. 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. 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. 4. Readmission rateAuthor, year Outcome 1 Outcome 2Koelling, Johnson, Cody Fewer days in hospital Reduced risk of& Aaronson, 2005 readmissionKrumholz, Amatruda, Reduced risk of Fewer days in hospitalSmith, Mattera, readmissionRoumanis, Radford,Crombie & Vaccarino,2002Kwok, Lee, Woo, Lee & Reduced risk ofGriffith, 2008 readmissionDomingues, Clausell , Reduced number ofAliti, Dominguez & visits to the emergencyRabelo, 2011 room
    5. 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. 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. 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 significantEffect Intervention Control g Reductio (P-value and or g n CI)Possiblity 1 x (n) y (n) % valuePossiblity 2Possiblity 3Possiblity 4Possibilty 5
    8. 8. Example of measure Patients who readmission to the ward n=100, 50 in each groupEffect Intervention g Control g ReductionNo readmission 20 10 -50%One or more 10 20 +50%readmissionTwo or more 10 10 -readmissionReadmission but 5 5 -because of somethingelseDied 5 5 -
    9. 9. Visualize with a line chart Add time as a variable  Knowledge is temporary (Koelling, et al., 2005). Useful to measure variables over timeReadmission rate a/b Y-Values Linear (Y-Values) Time
    10. 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