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Cheryl L. Damberg, PhD, Kristiana Raube, PhD, Stephanie Teleki, PhD, and Erin dela Cruz

Rewarding Performance: Three-Year Results from California's Statewide Pay-for-Performance Experiment. Cheryl L. Damberg, PhD, Kristiana Raube, PhD, Stephanie Teleki, PhD, and Erin dela Cruz June 5, 2007. Financial support provided by the California Healthcare Foundation. Presentation Topics.

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Cheryl L. Damberg, PhD, Kristiana Raube, PhD, Stephanie Teleki, PhD, and Erin dela Cruz

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  1. Rewarding Performance: Three-Year Results from California's Statewide Pay-for-Performance Experiment Cheryl L. Damberg, PhD, Kristiana Raube, PhD, Stephanie Teleki, PhD, and Erin dela Cruz June 5, 2007 Financial support provided by the California Healthcare Foundation

  2. Presentation Topics • IHA Pay-for-Performance program design • Year-to-year changes in performance scores • Physician group responses to P4P post 3rd incentive payment • Conclusions

  3. Evaluation of the IHA P4P Program • A 5-year evaluation to assess the impact of the IHA P4P program on: • Changes in performance over time • Changes in payments and the distribution of payments over time • The relationship between structural characteristics and performance scores • Physician group responses to the incentive program • Leadership interviews with physician groups

  4. IHA P4P Program • A statewide collaborative effort among: • 7 major health plans and 225 medical groups • 12 million commercial HMO and POS enrollees • Measurement started in 2003 for 1st payout in 2004 • 3rd payout occurred late summer 2006

  5. Performance Measures MY Year 2005, Payout 2006 • Clinical • Asthma management • Childhood immunization (MMR, VZV) • Cancer screening (breast, cervical) • Diabetes (HbA1c measure and control) • LDL (screening and control: 03 cardiac; 04 cardiac and diabetic) • Patient Experience • Timely access to care • Doctor-patient interaction/communication • Specialty care • Overall ratings of care • IT Capability • Integrate clinical electronic data for population management • Clinical decision making support at point of care through electronic tools

  6. Weighting of Measures in Payout Formula

  7. Changes in Payouts: 2004-2006 ∆=47% increase in IHA portion

  8. Total Payments to Physician Organizations*2004 vs. 2005 * Note: Truncated to groups receiving less than $2 million

  9. 3-Year Performance Changes 2003 (2004 payout) to 2005 (2006 payout)

  10. Modest Changes in Patient Experience Scores Statistically significant at *** p<.001 ** p < .01; * p < .05

  11. Asthma: All Ages 21% point gain in performance Reduction of 5.6% points in variation

  12. Breast Cancer Screening 3.5% point gain in performance Reduction of 2.3% points in variation

  13. HbA1c Screening 7.7% point gain in performance Reduction of 19.8% points in variation

  14. Diabetes HbA1c Screening: 2004 vs. 2005

  15. Breast Cancer Screening: 2004 vs 2005

  16. IT adoption increases each year By 2005, 33-44% of Groups and 68-76% of Patients Had Data Integration Technology

  17. More IT Functions are Adopted By 2005, 1-39% of Groups; 20-64% of Patients had Point of Care Technology

  18. Physician Organization Responses to Pay for Performance:Findings from Leadership Interviews

  19. Physician Organization Responses to the Incentive Program • Second round of interviews with physician leadership (3 years into program) • Study population: 35 physician organizations (POs) out of a universe of 225 in CA (n=29 completed to date) • Cross section of groups • High, medium, and low performing Pos • Reflects the spectrum of “winners and losers” • Large and small POs • Reflects resource constraints • Rural and urban POs

  20. Support Quality Focus, but Face Constraints • Most said the organization provides support to addressing quality • Mean score = 4.0 (1 to 5 scale, with 5 = a lot of support) • Biggest constraints to improving quality: • Technology challenges, such as lack of EMR • Changing physician behavior • Data issues, such as data integration, missing information, etc. • POs feel they are moderately successful in monitoring their quality performance • Mean score=3.7 ( 1-5 scale, with 5 = very successful)

  21. Is the Current Incentive Level of 1-2% of Capitation Right? • Among those earning incentives, the amount was 2% or less as a percentage of total capitation payments • Mixed results on +/- ROI • Widespread support for increasing incentives to 5-10% of capitation payments (26 out of 29 POs agreed) • This level would increase attention, provide a positive ROI and defray set-up costs • Some POs noted current levels have gotten their attention and urged them to make changes

  22. Most POs Believe P4P Affects Organizational and Physician Behavior • Increased organizational accountability for quality • New project managers, quality support, and medical directors • Improvements in data collection, including IT adoption • IT and data support staff • Data mining capabilities • EMRs, hardware, software, and web interfaces • Physicians are more directly managing patients and working with administration to improve quality • Bonuses tied to quality • Outreach to physicians; clinical and patient satisfaction guideline review

  23. Conclusions • Modest positive changes occurring for most measures • Combination of quality improvements and improvements in data capture • Data capture continues to challenge small groups and some IPAs • Challenges of how to improve patient experience • Performance payments have grown slowly over time • $$ at risk for performance are still a small fraction of total payments • Current level of incentives isn’t high enough to really get attention of physicians • Hard to incentivize specialists given absence of measures

  24. Will P4P Solve the Cost and Quality Problems in the U.S. Health System? • Improving the reliability of care received from current level of one-sigma to six-sigma? • Slowing the growth in healthcare costs to the rate of growth in the GDP or general level of inflation? • Reducing the number of deaths from medical errors from estimated rate of >100,000/year to below 5,000/year? • Unlikely in near term • Need for other policy levers in conjunction with P4P (e.g., broader performance measurement, transparency, investments in information systems)

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