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Making Value-Based Pricing A Reality: Issue Panel
Moderator: Meindert BoysenPanelists: John Brazier, Roberta Ara
and Werner Brower
ISPOR 16th Annual European Congress 2-6 November 2013, The Convention Centre in Dublin, Eire
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)
XOR
New drug Other use (?)
Cost:…………………………………………………………………………..
Cost / QALY:……………………………………………………………………..
->QALYs gained:…………………………………………………………………..
BoI weight:……………………………………………………………………
WSBs, £:…………………………………………………………………….
->WSBs, QALYs:…………………………………………………………………
-> Total Benefits:…………………………………………………………………
->Weighted QALYs:…………………………………………………………………
(£50k displaced)£50k
2 lost
£25k (centre of threshold range)
2 gained
£25k (measured ICER)
+30%
£12,000
2.8 QALYs’ worth gained
0.2 QALYs worth
2.6
+20%
£30,000
2.9 QALYs’ worth lost
0.5 QALYs worth
2.4
=
< X
£25,000 *1+ 0.1
£24,138
Comparing new and displaced treatments in VBP:Expression as an adjusted cost per QALY threshold
Adjustment to c/Q threshold:
30%+
1+ 0.2520%+=
Elicitation of societal preferences for Burden of Illness, Therapeutic
Improvement and End of Life from a UK online panel
John BrazierDH PRU in Economic Evaluation of Health and Care Interventions
(EEPRU), University of Sheffield
Donna Rowen, Clara Mukuria, Sophie Whyte, Anju Keetharuth, Aki Tsuchiya, Phil ShackleyHealth 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)
Outline of presentation
• Value-based pricing: BOI, TI and EOL• Methods• Main results • Weights for use in DH framework • Discussion
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)
Conceptual framework
Normal life expectancy
Normal population
Life expectancy from today
TodayDead
100%
Health
Without treatment
Conceptual framework
Normal life expectancy
Life expectancy without treatment
Health without treatment
Normal population
Life expectancy from today
TodayDead
100%
Health
Without treatment
Conceptual framework
Normal life expectancy
Life expectancy without treatment
Survival gain
Health without treatment
Health gain Treatment gain
Normal population
Life expectancy from today
TodayDead
100%
Health
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
1
FEEDBACK
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
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
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%)
Regression resultsVARIABLES 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***
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
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
Model (2) Allowing value of a QALY to vary
Warning: This is additive and not proportionate to the size of QALY gain
QALY gain
MRS(2)
0.05 - 0.063
0.1 - 0.063
0.5 - 0.063
1 - 0.064
2 - 0.066
5 - 0.073
10 - 0.087
20 - 0.141
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
To download the report go to:
http://www.eepru.org.uk/VBP%20survey%20research%20report.pdf