Eliciting societal preference for burden of illness, therapeutic improvement and end of life
Download as PPTX, PDF0 likes762 views
The document discusses value-based pricing (VBP) in healthcare, focusing on how to incorporate burden of illness (BOI), therapeutic innovation (TI), and end-of-life (EOL) considerations into pricing models. It presents a framework for adjusting cost per quality-adjusted life year (QALY) thresholds, supported by survey results from a UK online panel assessing societal preferences regarding these factors. The findings highlight the significance of QALYs, but also indicate that the effectiveness of BOI and TI in influencing pricing decisions is inconsistent.
Eliciting societal preference for burden of illness, therapeutic improvement and end of life
- 1. Making Value-Based Pricing A Reality: Issue Panel Moderator: Meindert Boysen Panelists: John Brazier, Roberta Ara and Werner Brower ISPOR 16th Annual European Congress 2-6 November 2013, The Convention Centre in Dublin, Eire
- 3. Value-based pricing: wider considerations • There is a ‘basic’ NHS cost per QALY threshold • Costs and QALYs (through weighting) to take into account: – diseases with greater ‘burden of illness’ as reflected in QALY loss from a condition – greater therapeutic innovation and improvement (size of QALY gain) – wider societal benefits (e.g. productivity and carer time) • Basic threshold adjusted to reflect the opportunity cost of displaced activities weighted using same methods • Price negotiated on the basis of the cost per weighted QALY compared to the new threshold (from 2014)
- 4. Comparing new and displaced treatments in VBP: Expression as an adjusted cost per QALY threshold Adjustment to c/Q threshold: £25,000 * New drug 1+ 30%+ 0.1 = £24,138 1+ 20%+ 0.25 Other use (?) OR X Cost:………………………………………………………………………….. £50k (£50k displaced) £25k (measured ICER) £25k (centre of threshold range) Cost / QALY:…………………………………………………………………….. ->QALYs gained:………………………………………………………………….. 2 gained 2 lost = BoI weight:…………………………………………………………………… +20% +30% ->Weighted QALYs:………………………………………………………………… 2.6 2.4 WSBs, £:……………………………………………………………………. £12,000 £30,000 ->WSBs, QALYs:………………………………………………………………… 0.2 QALYs worth 0.5 QALYs worth -> Total Benefits:………………………………………………………………… 2.8 QALYs’ worth gained < 2.9 QALYs’ worth lost X
- 5. Elicitation of societal preferences for Burden of Illness, Therapeutic Improvement and End of Life from a UK online panel John Brazier DH PRU in Economic Evaluation of Health and Care Interventions (EEPRU), University of Sheffield Donna Rowen, Clara Mukuria, Sophie Whyte, Anju Keetharuth, Aki Tsuchiya, Phil Shackley Health Economics and Decision Science, ScHARR, University of Sheffield Arne Risa Hole Economics Department, University of Sheffield Acknowledgements: Angela Robinson (University of East Anglia) and Gavin Roberts (DH)
- 6. Outline of presentation • • • • • Value-based pricing: BOI, TI and EOL Methods Main results Weights for use in DH framework Discussion
- 7. Elicitation of societal preferences Discrete choice experiment (DCE) survey using online UK panel to elicit societal preferences for: • Burden of illness (QALY loss from condition) • Therapeutic improvement (size of QALY gain from treatment) • End of life (e.g. NICE weights QALY gain more where expected survival is 24 months and survival gain 3 months or more)
- 8. 100% Conceptual framework Normal population Health Dead Today Normal life expectancy Life expectancy from today
- 9. 100% Conceptual framework Normal population Health Health without treatment Dead Today Without treatment Life expectancy without treatment Life expectancy from today Normal life expectancy
- 10. 100% Conceptual framework Normal population Health gain Treatment gain Health Health without treatment Dead Today Without treatment Life expectancy Survival gain without treatment Life expectancy from today Normal life expectancy
- 11. Main survey design • Internet panel sample – allows for large numbers, collection fast Survey content • • • • Introduction video played 2 practice and 10 real DCE questions 9 questions asking general attitudes assessed in survey 17 questions on ‘you and your health’ and understanding Design • 4 normal life expectancies (5, 20, 40, 80 years) • Both small and large starting point and gains in health and survival • 580 pairs selected using D-efficient design. Impossible scenarios not included • 58 ‘card blocs’ in total across 4 normal life expectancies
- 12. 1
- 13. FEEDBACK
- 14. Modelling • U=f(QALY gain, QALY gain squared, EOL or BOI) • Estimation by conditional logit regression model • Dependent variable = Choice patient group A or patient group B • Estimated for pooled data and each of the 4 separate normal life expectancies Basic additive model: V = β1 QALY + β2 QALY2 + β3 BOI (or EOL) Where a positive β2 would suggest TI
- 15. Marginal rate of substitution The marginal rate of substitution between BOI and QALY (or EOL and QALY) provides a measure of the weight of BOI in terms of QALY gain equivalents e.g. MRS1 = -β3 /β1 MRS2 = -β3 /(β1+ 2*β2QALY) So MRS2 varies by size of QALY
- 16. Main results (1) Sample • 3669 respondents (55% response rate) • Similar age, but more females and unemployed respondents and less healthy than UK norm Practice questions • PQ1 – Majority chose larger QALY gain (90.7-92.5%) • PQ2 - No evidence of preference for higher BOI (46.8% - 54.3%)
- 17. Regression results VARIABLES All 5 yrs 20 yrs 40 yrs 80 yrs QALY 0.276*** 3.641*** 0.751*** 0.404*** 0.171*** QALY_sq -0.004*** -0.709*** -0.037*** -0.014*** -0.002*** BOI 0.017*** 0.12*** -0.000 0.039*** 0.005** VARIABLES All 5 yrs 20 yrs 40 yrs 80 yrs QALY 0.281*** 3.229*** 0.761*** 0.400*** 0.175*** QALY_sq -0.004*** -0.602*** -0.037*** -0.014*** -0.002*** EOL 0.609*** 0.607*** 0.375*** 0.576*** 0.314***
- 18. Overview of results Regression results: • QALYs matter but at a decreasing rate – no support for TI • BOI matters – but is weak and inconsistent • EOL is significant • Coefficients change for different variants of normal life expectancy
- 19. Weights for BOI Model (1): Assuming the value of a QALY is constant • MRS(1) of 1 more unit of BOI is -0.040 QALYs Warning: This is additive and not proportionate to the size of QALY gain MRS(2) 0.05 - 0.063 0.1 Model (2) Allowing value of a QALY to vary QALY gain - 0.063 0.5 - 0.063 1 - 0.064 2 - 0.066 5 - 0.073 10 - 0.087 20 - 0.141
- 20. Limitations • • • • Limited range of characteristics (e.g. no age) Online data collection Additive design Robustness - many respondents may have continued to make the mistake of assuming the profiles were for them even after feedback – Identified respondents who chose a profile with smaller QALY gain and lower BOI but larger number of lifetime QALYs – Once these were excluded (n=2247) then BOI coefficients were all positive, significant and larger than for the whole sample • Weights – choice of variant and specification
- 21. To download the report go to: http://www.eepru.org.uk/VBP%20survey%20res earch%20report.pdf