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Measuring Progress in Patient Safety

Measuring Progress in Patient Safety. Peter Pronovost, MD, PhD, FCCM Johns Hopkins University. Exercise Please answer each question with a score of 1 to 5. 1 is below average, 3 is average and 5 is above average. How smart am I How hard do I work How kind am I How tall am I

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Measuring Progress in Patient Safety

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  1. Measuring Progress in Patient Safety Peter Pronovost, MD, PhD, FCCM Johns Hopkins University

  2. ExercisePlease answer each question with a score of 1 to 5. 1 is below average, 3 is average and 5 is above average • How smart am I • How hard do I work • How kind am I • How tall am I • How good is the quality of care we provide

  3. Improving Sepsis Care(n= 19 ICUs) 36% Reduction (NS) 69% Reduction (p < 0.001)

  4. Improving Sepsis Care(n= 19 ICUs) 36% Reduction (NS) 69% Reduction (p < 0.001)

  5. x Central Mandate Scientifically Sound Feasible Local Wisdom

  6. Conceptual model for measuring safety Structure Process Outcome Context Have we created a culture of safety? How often do we harm? Have we reduced the likelihood of harm? How often do we do what we are supposed to? IT Adapted from Donebedian

  7. Keystone ICU Safety Dashboard Pronovost JAMA 2007

  8. Pronovost BMJ 2008

  9. Comprehensive Unit-based Safety Program (CUSP) • Educate staff on science of safety http://www.jhsph.edu/ctlt/training/patient_safety.html • Identify defects • Assign executive to adopt unit • Learn from one defect per quarter and implement teamwork tools Pronovost J, Patient Safety, 2005

  10. What can be measured as a valid rate? • Rate requires • Numerator- event • Denominator- those at risk for event • Surveillance for events and those at risk • Minimal and Known Error • Random error • Systematic error

  11. Sources Variation in Safety measures • True variation in Safety • V data quality/definition/methods of collection • V case mix • V historical rates • Chance

  12. Measuring Preventable Harm • Measure rate or counts directly • High sensitivity low specificity • Estimate observed/expected (O/E) • Low sensitivity and specificity • Link process and outcome • High specificity and moderate sensitivity

  13. Process Measures • Validity of the construct • Validity of how we measure construct

  14. It is Ok to have non-rate measures Self reported measures are generally not valid as rates A common mistake is interpreting a non-rate measure as a valid rate

  15. Learning from Mistakes • What happened? • Why did it happen (system lenses) • What could you do to reduce risk • How to you know risk was reduced • Create policy/process/procedure • Ensure staff know policy • Evaluate if policy is used correctly Pronovost 2005 JCJQI

  16. Patient Safety Learning Communities • Identify Hazards • ( 4. Evaluate Effectiveness of Risk Reduction 2. Analyze & Prioritize Hazards 3. Mitigate Risks Patient safety learning communities relate to each other in a gear like fashion: as the identified hazards require stronger levels of intervention to achieve mitigation, the next learning community is engaged in action, eventually feeding back to the group that provided the initial thrust. Each group (unit, hospital, industry) follows the same four- step process, but they engage unique matrices of stakeholders to mitigate hazards that are within their locus of control. Pronovost Health affairs in press

  17. CAST • Each contributing factor rate • importance of the problem and contributing factors in causing the accident • importance of the problem and contributing factors in future accidents • Each Intervention rate • How well the intervention solves the problem or mitigates the contributing factors for the accident • Rates the team belief that the intervention will be implemented and executed as intended

  18. What is Culture*?: “The way we do things around here” • 1 attitude = opinion…everyone’s attitude = culture *aka Climate

  19. Executive Perceptions vs. Frontline Perceptions: Executives overestimate: Teamwork Climate 4X Safety Climate 2.5X Executive Confidence vs. Executive Accuracy: -Often wrong but rarely in doubt… -Currently no incoming data-streams -Halo Effects -Frontline data fills the gap

  20. * * * * * * * Statistically Significant

  21. 71 Teamwork Climate 2008 67 Teamwork Climate 2007 64 Teamwork Climate 2006 62 Teamwork Climate 2005

  22. 70 Safety Climate 2008 65 Safety Climate 2007 60 Safety Climate 2006 59 Safety Climate 2005

  23. #4. “I Would Feel Safe Being Treated Here As A Patient.” % of respondents within an ICU that agree

  24. #3. “Nurse Input Is Well Received In This ICU.” % of respondents within an ICU that agree

  25. #26. “In This ICU, It Is Difficult To Speak Up If I Perceive A Problem With Patient Care.” % of respondents within an ICU that agree

  26. #32. “Disagreements In This ICU Are Resolved Appropriately (i.e. not who is right, but what is best for the patient).” % of respondents within an ICU that agree

  27. Questions for Reflection • How do you know you are safer? • How will you become more efficient in your measurement efforts? • How will you better tap into local wisdom?

  28. Focus and Execute

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