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Value based purchasing in pharma - framework and case studies 20DEC17

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Pharma needs to consider a new reimbursement model that aligns with the value-based care payment models that other healthcare stakeholders are embracing. This short presentation provides a framework for discussion highlighting what's at stake for pharma and how pharma can move towards a true value-based reimbursement model.

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Value based purchasing in pharma - framework and case studies 20DEC17

  1. 1. the road to value-based purchasing in pharma framework and case studies wayne pan, md phd mba wtp94015@gmail.com photo credit: https://media.licdn.com/mpr/mpr/AAIAAQDGAAAAAQAAAAAAAA2JAAAAJGZiZTY1NjBjLWI5YmQtNGYxOS1iMTY5LTk5YmY4MTZlODFkYg.jpg
  2. 2. ME WE US all about it’s aboutcan be friends
  3. 3. no risk partial risk full risk framework traditional reimbursement for drugs based on units of utilization (fee-for-service) formulary placement, prior authorization, step edits, co-pays contracting, rebates, provider detailing, DTC advertising, co-pay assistance revenue model payor management pharma commercial strategies reimbursement for drugs based on performance to label or other clinical outcome (advanced fee- for-service) identification of patient population, enrollment into “program,” collecting clinical data to support rebate program targeting population, clinical data analysis, contracting, rebates, provider detailing annualized total spend on a specific therapeutic area, paid on a captitated basis (value-based purchasing) identification of patient population, enrollment into “program,” partnering to improve patient outcomes population health approach, clinical data analysis, clinical programs to manage population at risk
  4. 4. framework metrics stakeholder behavior pharma clinical strategies market share population diseased diseased at risk & diseased no risk partial risk full risk
  5. 5. framework pros cons no risk partial risk full risk most experience with this reimbursement model; status quo; no need to make any changes other pharma companies already doing this so it’s a less controversial step; we are gaining experience with this model through our efforts in innovative contracting expands our reach to the entire population, not just the diseased population; enables us to become true partners with providers and patients; aligns incentives with the rest of the healthcare ecosystem; reduces knowledge barriers between bench and bedside; solves biosimilar “problem” biosimilars will put pressure on pricing; entering into more crowded markets will put pressure on pricing; customers are moving to value-based purchasing and we would still be perceived as only a vendor and not a partner may not distinguish innovator from biosimilar manufacturers, so pricing pressure will still be there; reducing pharma revenue to only those patients for which the drug demonstrates effectiveness may inhibit pharma from moving to full risk as it will reduce overall budget in the therapeutic area still needs regulatory waivers to operate; we do not have infrastructure to manage entire population; unsure whether providers and patients will trust pharma as a partner
  6. 6. case study: advanced fee-for-service PFP contracts signed by Harvard Pilgrim, which is the leading insurer, and one of the very few, to pursue PFP contracts. In November 2015, Amgen agreed to provide Harvard Pilgrim with two PFP rebates if its evolocumab (Repatha), one of the two new proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, failed to meet two separate thresholds. In June 2016, Harvard Pilgrim signed two more PFP deals. In one it obtained a discount from Novartis if its new sacubitril/valsartan (Entresto) treatment for congestive heart failure does not yield a specified drop in hospitalizations. In the other, Harvard Pilgrim agreed to accept a lower rebate from Eli Lilly if its dulaglutide (Trulicity) diabetes drug lowers hemoglobin A1c (HbA1c) levels—a common way to track the disease—better than rival medicines. from: “Rewarding Results: moving forward on value-based contracting for biopharmaceuticals,” Network for Excellence in Health Innovation (NEHI), March, 2017
  7. 7. case study: advanced fee-for-service
  8. 8. case study: advanced fee-for-service
  9. 9. case study: advanced fee-for-service outcomes-based contract for Avastin® (bevacizumab)  in patients with non– small-cell lung cancer (NSCLC) The operational requirements of outcomes-based contracts can be daunting. The payer is responsible for tracking an individual patient’s health status and for collecting and reporting patient-level longitudinal data. However, most payer systems cannot evaluate specific clinical and outcomes data. For example, a payer claims system may indicate when a patient discontinues a medication, but not why --- a major stumbling block if PFS is the agreed- upon endpoint in the contract. Determining whether the discontinuation was due to clinical progression, toxicity, patient or provider preference, or some other reason often requires gaining access to the electronic health record (EHR), which many payers don’t have. Granting such access to payers can create privacy concerns. Even with access to EHR data, payers may face challenges, such as missing data fields or pertinent data documented in nonreadable text fields. If a provider’s EHR system does not capture the desired endpoint, line of therapy, indication for which a drug is prescribed, or medication dose, it may be difficult for the payer to gain maximum benefit from the contract --- either because of missing data or because of the overhead incurred in extracting data from text fields or chart reviews. As these challenges suggest, it is important to balance specificity with simplicity. If complexity makes operationalizing the contract impractical or cumbersome, either the manufacturer or the payer may be unwilling to enter into an agreement. Outcomes-based agreements are a natural extension of a health care delivery-and-reimbursement environment that is moving toward value. With provider organizations taking increasing accountability for both costs and outcomes, 
 it is becoming incumbent upon manufacturers to demonstrate the economic, clinical, and quality-of-life benefits of their medicines. The pilot described here was successful in that Genentech and Priority Health both learned how to overcome clinical, operational, and contractual challenges and demonstrated that this type of agreement is feasible.  Overcoming Challenges of Outcomes-Based Contracting for Pharmaceuticals: Early Lessons From the Genentech-Priority Health Pilot John Fox, Marc Watrous Although not a panacea, outcomes-based contracts may be a useful tool in aligning cost and value, driving health care efficiency, and ensuring that appropriate patients benefit from innovative medicines.
  10. 10. ? case study: value-based purchasing
  11. 11. profit = x% x ( ) + y% x (total cost of care) steps to value-based purchasing pilot 3) develop clinical strategy to manage population (in partnership with providers and patients) to keep costs within budget and hit quality metric target(s) Based on company knowledge of a particular disease area, how providers are managing that disease, how patients are diagnosed and treated, what are the gaps in quality/care, our relationship with partners who can help manage this population, ability to influence provider/patient behavior, understanding drivers of total costs of care 4) structure contract based on confidence in our ability to manage the population (shared savings model - upside only, up- & downside, risk for just therapeutic drugs, drug risk+ some risk for total cost of care (TCC)), auto-renews if targets met average monthly therapeutic area expenses during prior two years + small adjustment for aging population total therapeutic budget paid as PMPM 𝝙 between budget and actual spend profit = 0 quality gate quality metric targets NOT MET quality metric targets MET if “x” = 100 - full confidence if “x” < 100 - partial risk if profit ≥ 0 - upside only if “y” ≥ 0 - includes TCC scenarios: 2) calculate total therapeutic budget and specify quality metrics to measure management effectiveness across the entire at-risk population 1) select a pilot disease state