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Translating Evidence into Benefit for Patients The Impact of Clinical Leadership and Culture

Translating Evidence into Benefit for Patients The Impact of Clinical Leadership and Culture. Sharon Levine, M.D. Kaiser Permanente, California November, 2003. Kaiser Permanente. An “outsider” model of care delivery from the beginning

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Translating Evidence into Benefit for Patients The Impact of Clinical Leadership and Culture

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  1. Translating Evidence into Benefit for Patients The Impact of Clinical Leadership and Culture Sharon Levine, M.D. Kaiser Permanente, California November, 2003

  2. Kaiser Permanente • An “outsider” model of care delivery from the beginning • Prepayment to a multi-specialty group practice: suspect from the beginning • Early ostracism: exclusion from participation in organized medicine (AMA, county medical societies) • Gradual acceptance after four decades • In the last decade, acknowledgment and respect: ability to measure and demonstrate superior outcomes

  3. Organizational structure and relationships essentially unchanged since 1955 • “Integrated delivery system” • Relationships - Contractual - Partnership of equals - Mutually exclusive - Shared fate • Co-ownership: shared accountability for success of the whole

  4. An Evidence-Based Approach to Effective and Efficient Care DeliveryScience and Sociology • Science: Identify the “right thing” (30%) • Systematic reviews of the evidence • Epidemologic research • Outcomes measurement and identification of successful practices • Evidence-based, clinical practice guideline development • Design and development of care management programs for selected clinical priorities (eg., asthma, diabetes) and populations (eg., frail elderly)

  5. Translating Evidence into BenefitThe Science (30%) Research Evidence Implementation Benefit Epidemiology Care Management Institute Health Services Research Drug Information Services Clinical Research

  6. Translating Evidence into BenefitSociology (70%) Research Evidence Implementation Benefit • Integration • Aligned Incentives • Balanced Incentives Structure Culture • Physician Leadership • Culture of accountability, commitment, pride, performance Infrastructure • Systems support: from paper to electronic • Information and data • Education

  7. Integration Along Multiple Dimensions • Financing and Care Delivery: Single revenue stream, shared responsibility for allocation • Across the continuum of care (community, out-patient, in-patient, home care) and between primary care and specialty care • Integration over time: Investment mind set, long time horizons • Across the continuum of an illness or condition: primary and secondary prevention, diagnostic and therapeutic services, supportive care, palliative care

  8. Aligned Incentives • Health Plan, Hospitals, Medical Group • Shared fate, mutual exclusivity • Partnership of equals • Primary care and specialist physicians: Co-located practice; shared ownership of patients/clinical problems; facilitated referrals (e-Consult) • Hospitalists providing inpatient care • Balanced Incentives • No “production” incentives • No reward, incentive/personal benefit for under-utilization • Prepayment/capitation to the Medical Group; salary for physicians • Incentives based on quality outcomes and patient satisfaction

  9. Physician Leadership • Self-governed, self-managed Medical Group • Physicians manage all aspects of the business of the Medical Group • “Every Physician a Leader” • 25-30% of physicians with some management responsibility, administrative title • Explicit effort to recruit physicians with leadership potential, leadership traits • Leader’s role: actively manage the culture • Group Responsibility • Culture of shared accountability for quality and cost of health care • Peer accountability: collaborative practice, common chart; transparency of performance data; • Ownership of the problems and the solution • Culture of commitment, not compliance

  10. Systems Support • Many pieces currently in place • e-Consult, e-Rx, e-Refill • CIPS (Clinical Information Presentation System) • Awaiting full implementation of electronic medical record (KP Health Connect)

  11. Using Clinical Information Systems • Preventive Health Prompt • PILOT • Patient Encounter data (OSCR) • Disease registries • Electronic Medical Record

  12. Substantial Investment in Career-Long Education and Professional Development • Continuing medical education • Clinician patient communication • Management training • Leadership Development • Systems training and support • Training for collaborative practice/team-based care • Education/information in lieu of regulation/prior authorization

  13. Translating Evidence into BenefitThe Results Research Evidence Implementation Benefit • Patient • Better clinical outcomes • Longer, more functional life • Safer care • System • Increased efficiency • Reputation • Fewer errors, rework • People • Professional satisfaction • Pride • Reputation • Commitment

  14. FOCUS ON THE CRITICAL FEW

  15. CARDIOVASCULAR DISEASE: • Leading cause of death in U.S. • 10 Year effort to implement national guidelines for hyperlipedemia, CHF, ACS, cardiac rehabilitation, and reduce cardiovascular mortality • Multi-disciplinary steering group • Physician champion for each guideline at each facility • Low Tech: Preprinted orders for ER, hospital; algorithms for outpatient treatment • RN and Pharm D.-run cholesterol, cardiac rehabilitation and congestive heart failure programs

  16. CARDIOVASCULAR DISEASE: • High tech: CAD registry, CHF registry with intelligent software system for outreach and tracking • CAD registry linked to registration system, with prompts at visit for cholesterol check; also to PILOT (patient integrated log, outreach and tracking) to generate “outreach” report with patient’s LDL, beta-blocker and aspirin use, provided quarterly to physicians

  17. RESULTS: PROCESS GOALS • By 2000, 99% use of beta-blockers in post MI patients at discharge, 80% at 1 year, 77% at 2 years • LDL control < 130 improved from 22% to 84% in post-MI patients (1996-2002) • ASA at discharge for post-MI patients 93% • 72% of CHF registry patients on vasodilators • 64% of CHF patients on beta blockers

  18. RESULTS: OUTCOME GOALS • 15% decrease in death rate from CHF (1996-2001) • 25% decrease in CHF discharge rate (1998-2001) • Age/sex/risk adjusted mortality rates for KFH hospitals declining 50-85% since 1993 • MI mortality rates up to 50% lower than similar hospitals across the state participating in National Registry of Myocardial Infarction (NRMI) • Heart disease mortality more than 30% lower in the KPNC population than in the non-KPNC population (after age and sex adjustment)

  19. The Healthy People 2010 goal for adult smoking prevalence is set at 12%. The California’s Tobacco Control Program in its 2003-2005 Master Plan, aims to reduce adult tobacco prevalence to 13% by 2005. The long-term California goal is to reduce adult tobacco prevalence to 10%. Source: Kaiser Permanente Division of Research - Preliminary Member Health Survey report prepared by Nancy P. Gordon, ScD, Division of Research 10/14/2003 Source: CDC-National Center for Chronic Disease Prevention & Health Promotion Behavioral Risk Factor Surveillance System 2002 19

  20. Translating Evidence into Benefit What Worked • Science: Sufficient evidence; high quality • Sociology: • Clinical peer leadership • Passionate champions • High engagement process • Decision support at the point of care across the continuum • Increasingly sophisticated technology • Practice support • Unblinded sharing of performance data (“healthy competition”) • Patient education, engagement • Perseverance

  21. CONCLUSION • A multi-modal, multi-specialty, clinician peer-expert-led implementation of national guidelines for cardiovascular disease management has led to a substantial decline in cardiovascular mortality • On an absolute basis, compared to non-KPNC mortality • On a relative basis, compared to cancer mortality

  22. Results: Cardiovascular Mortality Relative to Cancer Mortality 22

  23. 30-Day Mortality After Acute Heart Attack KP NCal hospitals vs . all other hospitals in counties with KP hospitals 25 = statistically sig. p<0.01 20 KP THE REST 15 13% 10 8% 5 0 Source: OSHPD

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