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Published on February 4, 2014

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Economic Evaluation of Health and Social Care Interventions Policy Research Unit Elicitation of societal preferences for Burden of Illness, Therapeutic Improvement and End of Life from a UK online panel Donna Rowen John Brazier, Clara Mukuria, Sophie Whyte, Anju Keetharuth, Aki Tsuchiya, Phil Shackley, Arne Risa Hole

Aims of presentation • • • • • Value-based pricing: BOI, TI and EOL Methods Main results Weights for potential use in NICE or DH framework Discussion

Value-based pricing: wider considerations • There is a ‘basic’ NHS cost per QALY threshold • Costs and QALYs (through weighting) to take into account: – conditions 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) (DH, 2010) • 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

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) (BOI) • Therapeutic improvement (size of QALY gain from treatment) (TI) • End of life (e.g. NICE weights QALY gain more where expected survival is less than 24 months and survival gain is 3 months or more) (EOL)

100% Conceptual framework Normal population Health Dead Today Life expectancy from today Life expectancy without the condition

100% Conceptual framework Normal population Health Health without treatment Dead Today Without treatment Life expectancy without treatment Life expectancy from today Life expectancy without the condition

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 Life expectancy without the condition

Preparatory work • Review on the social value of a QALY • Large preparatory online survey to pilot DCE and person trade-off questions • Qualitative survey to further explain the findings of the large preparatory online survey • Six-arm online and face-to-face survey examining different framings of questions and mode of administration • For further details see Brazier et al (2013)

Attributes to capture BoI, TI and EoL Attribute Levels No. of levels Life expectancy without condition 5, 20, 40, 80 4 (years) Life expectancy without treatment 3 months, 1 year, 2 years, 5 years, 7 (years) 10 years, 30 years, 60 years Survival gain from treatment 0, 3 months, 6 months, 1 year, 3 7 years, 10 years, 60 years Health before treatment (%) 10, 20, 40, 60, 80 5 Health gain from treatment (%) 0, 2, 5, 10, 30, 60 6 Note: Extra scenarios with small life expectancy without treatment and survival gains estimated for 5 years normal life expectancy

Attributes to capture BoI, TI and EoL •Same across pairs Attribute Levels Life expectancy without condition •Respondents see only 1 No. of •Scenarios selected using separate design for each levels level 5, 20, 40, 80 4 (years) Life expectancy without treatment 3 months, 1 year, 2 years, 5 years, 7 (years) 10 years, 30 years, 60 years Survival gain from treatment 0, 3 months, 6 months, 1 year, 3 7 years, 10 years, 60 years Health before treatment (%) 10, 20, 40, 60, 80 5 Health gain from treatment (%) 0, 2, 5, 10, 30, 60 6 Note: Extra scenarios with small life expectancy without treatment and survival gains estimated for 5 years normal life expectancy

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 life expectancies without the condition (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 life expectancies without the condition

1

FEEDBACK

Modelling • Estimation using conditional logit regression model with clustering of the standard errors at the respondent level • Dependent variable = Choice of patient group A or patient group B • Estimated for pooled data and each of the 4 separate life expectancies without the condition Basic model: V1 = β1 QALY + β2 BOI (or EOL) V2 = β1 QALY + β2 BOI (or EOL) + β3 QALY2 Where a positive β3 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 the QALY gain equivalent e.g. MRS1 = -β2 /β1 MRS2 = -β2 /(β1+ 2*β3QALY) So MRS2 varies by size of QALY

Main results Sample • 3669 respondents (55% response rate of those accessing the survey) • Representative for age and gender but more 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 results • QALYs matter but at a decreasing rate – no support for TI • BOI matters – but not always significant • EOL is significant • Coefficients change for different variants of life expectancy without the condition

Regression results for BOI VARIABLES All 5 yrs 20 yrs 40 yrs 80 yrs QALY 0.149*** 1.813*** 0.437*** 0.191*** 0.086*** BOI 0.006*** 0.068* -0.015 0.028*** -0.003 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**

Regression results for EOL VARIABLES All 5 yrs 20 yrs 40 yrs 80 yrs QALY 0.156*** 1.628*** 0.455*** 0.190*** 0.088*** EOL 0.521*** 0.871*** 0.359*** 0.479*** 0.152*** 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***

Weights for BOI • MRS(1) of 1 more unit of BOI is -0.040 QALYs 95% CI (-0.068, -0.013) • Generated using all data 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

Weights for EOL • MRS(1) of moving from not being EOL to being EOL is -3.331 QALYs 95% CI (-3.711, -2.950) • Generated using all data QALY gain MRS(2) 0.05 -2.170 0.1 -2.173 0.5 -2.197 1 -2.229 2 -2.294 5 -2.516 10 -3.000 20 -4.875

Attitudinal questions • Modal response across questions was that the same priority should be given to all patients • Overall responses indicated most respondents believed the NHS should give preference to the group with the largest treatment gain over BOI or EOL • Some support for BOI - approx 43% • Some support for EOL – approx 45-57% – only 6% if it is at the natural end of their life – only 4% if patients will live in very poor health • Little support for TI

Discussion • Social value of a QALY is not equal for all recipients • Results provide some support for BOI and support for EOL – Weights for BOI and EOL should not both be used – Finding for EOL contrary to Shah et al (2012) and Linley and Hughes (2013) • No support for TI – arguably consistent with literature • In attitudinal questions the modal response was that the same priority should be given to all patients – Questions do not involve trade-offs • Weights estimated using MRS using pooled data – choice of variant and specification affects results

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 (remaining n=2247) then BOI coefficients were all positive, significant and larger than for the whole sample

Summary • • • • Some support for BOI QALY gain matters – but no support for TI Support for EOL Social value of a QALY is not equal for all recipients

References • Brazier J, Rowen D, Mukuria C, Whyte S, Keetharuth A, Risa Hole A, Tsuchiya A, Shackley P. Eliciting societal preferences for burden of illness, therapeutic improvement and end of life for value based pricing. EEPRU Research Report 01/13, Universities of Sheffield and York; 2013 http://www.eepru.org.uk/VBP%20survey%20research%20report.pdf • Department of Health. Value based pricing: impact assessment. London. Department of Health; 2010 http://webarchive.nationalarchives.gov.uk/20130107105354/http://www. dh.gov.uk/en/Consultations/Liveconsultations/DH_122760. • Linley WG and Hughes DA. Societal views on NICE, cancer drugs fund and value-based pricing criteria for prioritising medicines: A cross-sectional survey of 4118 adults in Great Britain. Health Economics 2013;22: 948-964 • Shah KK, Tsuchiya A, Hole AR and Wailoo A Valuing health at the end of life: A stated preference discrete choice experiment. Report by NICE DSU; 2012

Economic Evaluation of Health and Social Care Interventions Policy Research Unit Elicitation of societal preferences for Burden of Illness, Therapeutic Improvement and End of Life from a UK online panel Donna Rowen John Brazier, Clara Mukuria, Sophie Whyte, Anju Keetharuth, Aki Tsuchiya, Phil Shackley, Arne Risa Hole Acknowledgements: Angela Robinson (University of East Anglia) and Gavin Roberts (DH)

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