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Pay-for-Performance: A Decision Guide for Purchasers

Pay-for-Performance: A Decision Guide for Purchasers . Guide Prepared for: Agency for HealthCare Research and Quality U.S. Department of Health and Human Services Prepared by: R. Adams Dudley, M.D., M.B.A. University of California San Francisco Meredith B. Rosenthal, Ph.D.

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Pay-for-Performance: A Decision Guide for Purchasers

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  1. Pay-for-Performance: A Decision Guide for Purchasers Guide Prepared for: Agency for HealthCare Research and Quality U.S. Department of Health and Human Services Prepared by: R. Adams Dudley, M.D., M.B.A. University of California San Francisco Meredith B. Rosenthal, Ph.D. Harvard School of Public Health

  2. Overview • Not a users manual: too little data • Addresses: • Developing an overall strategy • Incentive design and measures selection • Implementation • Evaluation and revision

  3. Is Our Community Ready? • Do we know what we are trying to accomplish? • Do we have enough influence? • Are the providers ready?

  4. Strategic Issues: Getting Started • Voluntary vs. mandatory: • Voluntary: easier, may only attract high-performing providers • Mandatory (i.e., written into all contracts): creates uniform incentives, but may need high market share • Bonus program is in between: “mandatory”, but providers are free to ignore it • Phasing in: start with volunteers, or “pay for participation”/“pay for reporting”

  5. Strategic Issues: Getting Started • Which providers to target?: • Hospitals and/or physicians • Large vs. individual/small group • Contribution of hospitals vs. physicians to quality and cost varies from region to region • Measurement issues favor larger groups but incentives may be stronger for individuals • System view of quality improvement suggests higher level • Choose the provider target for which you can get the biggest bang for your buck

  6. Increasing Inclusion of Specialists and Hospitals in Pay-for-Performance Source: Rosenthal et al., Climbing Up the Pay-for-Performance Learning Curve, Manuscript, Harvard University 2006.

  7. Choosing Measures • National measure sets should be considered first • Tested • Accepted • Already being collected • Some sources: AHRQ (Inpatient Quality Indicators), National Quality Forum, Hospital Quality Alliance, Ambulatory Care Quality Alliance, NCQA, Leapfrog Group

  8. Incentive Design Challenges • All P4P programs are not the same • Design choices matter • First critical question is orientation: • Quality improvement across all providers, patients? • Rewards for the best only? E.g., Premier Inc./CMS demonstration

  9. Explicitly or Implicitly Rewarding Quality Improvement • P4P programs that reward top group (e.g., 20%) or set a benchmark for reward that all must meet do not uniformly encourage improvement • These features should result in more QI: • Rewarding improvement explicitly (i.e. change rather than/in addition to level) • Multiple levels of rewards (partial credit) • Payments tied to each patient treated well

  10. Case Example: Hudson Health Plan: Rewarding Quality Diabetes Management

  11. Key Design Issues: How Much Money? • To be effective, bonus should be commensurate with cost of effort • Little good information about what it takes to reach quality targets • Most P4P programs for physicians 5-10% of associated fees; hospitals 1-2%

  12. Making the Business Case for Pay-for-Performance • Many P4P programs target under use of beneficial but not cost-saving therapies (e.g., cancer screening) • Purchasers increasingly want to orient programs toward efficiency or value – although providers may see such efforts as de-legitimizing

  13. Making the Business Case for Pay-for-Performance • For P4P to be cost neutral or cost saving programs have focused on: • Under use of treatments that have evidence of substantial cost offsets (e.g. result in reductions in hospitalization) • Over use of high-cost interventions (e.g., inappropriate surgery) • Misuse/errors that result in need for more services (e.g., avoidable complications) • Explicit cost or efficiency measures

  14. Increasing Emphasis on Outcomes, IT, Cost-Efficiency Source: Rosenthal et al., Climbing Up the Pay-for-Performance Learning Curve, Manuscript, Harvard University 2006.

  15. Planning Ahead for Evaluation • You spent all that time and money…shouldn’t you assess what you accomplished? • Aspects of implementation can facilitate evaluation • Collecting data during a measurement (i.e. non-payment) year will allow before/after comparison • Implementing P4P for some providers before others may create a natural comparison group

  16. What Types of Effects to Look For • Data collection should not only track intended consequences but also monitor potential side effects: • Patient selection/dumping (changes in case-mix, excessive switching) • Diversion of attention away from other important aspects of care • Widening gaps in performance between best and worst

  17. Summary • Pay-for-performance can facilitate improved patient care, cost-efficiency • Best practices still unknown • Careful matching of goals and mechanisms will most likely lead to best results • In light of uncertainties about design, evaluation is key

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