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The reference ICER for the Australian health system: estimation and barriers to use
- 1. adelaide.edu.au seek LIGHT The reference ICER for the Australian health system: estimation & barriers to use Dr Laura Edney (laura.edney@adelaide.edu.au) Professor Jon Karnon, Dr Hossein Afzali, Dr Terence Cheng
- 5. Professor Jon Karnon Dr Hossein Haji Ali Afzali Dr Terence Cheng Professor Annette Braunack-Mayer Dr Drew Carter University of York: Professor Mark Sculpher, Professor Karl Claxton, Dr James Lomas Advisory group members University of Adelaide 5
- 6. Overview University of Adelaide 6 Introduction
- 7. Overview University of Adelaide 7 Introduction Methods & Results
- 8. Overview University of Adelaide 8 Introduction Methods & Results Mortality- related QALYs
- 9. Overview University of Adelaide 9 Introduction Methods & Results Mortality- related QALYs Morbidity- related QALYs
- 10. Overview University of Adelaide 10 Introduction Methods & Results Mortality- related QALYs Morbidity- related QALYs Reference ICER
- 11. Overview University of Adelaide 11 Introduction Methods & Results Barriers to use Mortality- related QALYs Morbidity- related QALYs Reference ICER
- 12. Introduction • Spending on new healthcare technologies increases net population health only when the benefits of the new technology are greater than their opportunity costs School of Public Health, University of Adelaide 12
- 14. Introduction University of Adelaide 14 Empirical estimate of opportunity cost for English NHS £12,936 per QALY
- 15. Introduction University of Adelaide 15 Empirical estimate of opportunity cost for English NHS £12,936 per QALY
- 16. Introduction University of Adelaide 16 Empirical estimate of opportunity cost for English NHS £12,936 per QALY Empirical estimate of opportunity cost for Spanish NHS £21,421 per QALY
- 17. Context in Australia University of Adelaide 17
- 18. Total health expenditure in Australia (AIHW, 2015) ≈ $155b in 2013-14 (9.78% of total GDP) University of Adelaide 18 70,000 80,000 90,000 100,000 110,000 120,000 130,000 140,000 150,000 160,000 Constant prices to 2013-14 prices Total health expenditure ($ million) Context in Australia
- 19. Context in Australia • Between 2013/14 to 2015/16: – Commonwealth spending on patented pharmaceuticals increased by 27.2% – Script volume declined by 13.6% • These new pharmaceuticals may represent good value for money, but the basis for assessing value is limited by lack of empirical information on the opportunity cost of decisions to fund new health technologies University of Adelaide 19
- 20. Context in Australia • Constrained budget • Pharmaceutical Benefits Advisory Committee (PBAC) & Medical Services Advisory Committee (MSAC) – Provide recommendations to the Minister for Health on the value of new pharmaceuticals and medical services to the Australian taxpayer – No explicit threshold, but ‘value for money’ University of Adelaide 20
- 21. Context in Australia • Defining value for money: • PBAC – Public Summary Documents refer to conditional acceptance if ICERs reduced to $45,000 to $75,000 (£26,000-£43,000) – Point estimate provided to companies (commercial in confidence) • MSAC – Cost-effectiveness “remained acceptable [at an] ICER of ~$43,000 per QALY” (£25,000) • Do these thresholds represent value for money? University of Adelaide 21
- 22. Improvement in HRQoL from 2011-12 health spending Method: overall approach 22 Elasticity of quality-adjusted YLL to public health spending in 2011/12 Mortality- related QALYs Morbidity- related QALYs + Reference ICER Increased expenditure 2011- 12 / Mortality + Morbidity QALY gains
- 23. Improvement in HRQoL from 2011-12 health spending Method: mortality-related QALYs (1) 23 Elasticity of quality-adjusted YLL to public health spending in 2011/12 Mortality- related QALYs Morbidity- related QALYs + Reference ICER Increased expenditure 2011- 12 / Mortality + Morbidity QALY gains
- 24. Method: mortality-related QALYs • Statistical Local Areas (SLAs) of usual residence • Common unit of analysis to link data (n=1028) • Smallest geographical unit of the Australian Standard Geographical Classification • Based on bodies of local government, suburbs, areas of economic significance, specific localities or non-urban areas • Vary in size with an average estimated resident population of 20,000 • Health funds are not allocated to SLAs University of Adelaide 24
- 25. University of Adelaide 25
- 26. Method: mortality-related QALYs • Health spending is endogenous to health outcomes • First stage: – log ℎ𝑒𝑎𝑙𝑡ℎ 𝑠𝑝𝑒𝑛𝑑𝑖𝑛𝑔 = 𝛼 + 𝑐𝑜𝑣𝑎𝑟𝑖𝑎𝑡𝑒𝑠 + 𝑖𝑛𝑠𝑡𝑟𝑢𝑚𝑒𝑛𝑡 + 𝜀 • Second stage: – log 𝑄𝐴𝐿𝑌𝑠 𝑚𝑜𝑟𝑡𝑎𝑙𝑖𝑡𝑦−𝑟𝑒𝑙𝑎𝑡𝑒𝑑 = 𝛼 + log ℎ𝑒𝑎𝑙𝑡ℎ 𝑠𝑝𝑒𝑛𝑑𝑖𝑛𝑔 + 𝑐𝑜𝑣𝑎𝑟𝑖𝑎𝑡𝑒𝑠 + 𝜀 University of Adelaide 26
- 27. Method: mortality-related QALYs University of Adelaide 27 Health spending = Sum of spending across • Public hospitals • MBS • PBS $67b YLLLE = LE – age at death • Where LE=80 for males & 84 for females • +1 YLL for persons dying beyond life expectancy • Age and gender standardised • YLL weighted by age- and gender-specific utility scores (SF-6D) Generates QALYs lost per SLA Instrument = unpaid care • +ive relationship • ↑ unpaid care = ↑ health spending (needs adjusted) Rationale: • ↑ identification of need for services by carers, & • ↑ access to health services through removal of physical barriers to access
- 28. Method: mortality-related QALYs University of Adelaide 28 Healthcare need= Census-based variables (n=18) • Demographics • Socioeconomics • Health status Population density Females Males 15-24 years ATSI Born overseas Lone pensioner Concession card Government housing Volunteering Cost of living State/territory dummies Remoteness dummies Covariates
- 29. Results: mortality-related QALYs Diagnostic tests • Endogeneity – Hausman test (26.138, p<0.01) – Durbin-Wu-Hausman test (F(1,1004)=25.94, p<0.001) • Relevant instrument – Strong predictor of health spending in the first stage (β1=0.193, p<0.001) • Valid instrument – Appropriately excluded from vector of covariates in second stage – i.e. impact of instrument on QALYs lost occurs solely through health spending University of Adelaide 29
- 30. Results: mortality-related QALYs • Elasticity of mortality-related QALYs to health spending = 1.6 • 0.01 ∆ health spending = 0.016 ∆ mortality-related QALYs University of Adelaide 30
- 31. Results: mortality-related QALYs University of Adelaide Incremental cost per mortality-related QALY = 0.01.∑(health spending) / 0.016.∑(mortality-related QALYs) = $670M / 9,588 = $69,870 Annual per capita mortality-related QALY gain = ∆(per capita health spending) / incremental cost per mortality-related QALY = $90 / $69,870 = 0.0013 (95%CI= 0.0003, 0.0023) 31
- 32. Improvement in HRQoL from 2011-12 health spending Method: morbidity-related QALYs 32 Elasticity of quality-adjusted YLL to public health spending in 2011/12 Mortality- related QALYs Morbidity- related QALYs + Increased expenditure 2011- 12 / Mortality + Morbidity QALY gains Reference ICER
- 33. Method: morbidity-related QALYs • Household, Income & Labour Dynamics in Australia (HILDA) – Longitudinal nationally representative survey of Australian adults, 2002—2013 – N=68,873 University of Adelaide 33
- 34. Method: morbidity-related QALYs • Temporal change in HRQoL (SF-6D) – Fixed effects regression • Extensive range of covariates used to interpret coefficient on time trend as due to change in health spending – Demographics: marital status, 21 binary life events – Social: satisfaction with personal safety, local community, neighbourhood, free time, life in general – Economic: income, employment status, satisfaction with financial situation, perceived difficulty raising money for an emergency, etc. University of Adelaide 34
- 35. Method: morbidity-related QALYs • Not all change in HRQoL will be maintained across lifetime • HRQoL improvements either: – Require ongoing spending to be maintained (e.g. chronic conditions), or – Are maintained without additional spending in subsequent years (e.g. elective surgery) University of Adelaide 35
- 36. Method: morbidity-related QALYs • Reference ICER should capture all HRQoL improvement from a single year of healthcare spending • Therefore: 1. exclude ongoing effects of spending in years prior to 2011, & 2. incorporate ongoing effects of spending in 2011 on subsequent years University of Adelaide 36
- 37. Results: morbidity-related QALYs • Annual per capita change in HRQoL = 0.0026 (95% CI= 0.0019, 0.0033) • Aggregated weighted duration of HRQoL effects 2 – 4.1 years across 3 scenarios • Corresponding estimates of proportion of total health services that provide a lifetime HRQoL effect of 10.2% to 23.5% • Base case = central estimates of – Duration effects (from 1 year of health spending)= 2.5 years – Proportion of lifetime HRQoL effects = 11.7% • Annual per capita improvement in morbidity-related QALYs = 0.0066 University of Adelaide 37
- 38. Improvement in HRQoL from 2011-12 health spending Reference ICER 38 Elasticity of quality-adjusted YLL to public health spending in 2011/12 Mortality- related QALYs Morbidity- related QALYs + Reference ICER Increased expenditure 2011- 12 / Mortality + Morbidity QALY gains
- 39. Reference ICER University of Adelaide 39 = ∆ per capita health spending / (mortality + morbidity- related QALYs) = $219.9 / 0.0013 + 0.0066 = $28,033 per QALY (95% CI $20,758, $37,667) = £16,280 per QALY (95% CI £12,055, £21,875)
- 40. Deterministic Sensitivity Analysis • 2 key input parameters – Elasticity of mortality-related QALYs to health spending – Year trend representing per capita change in morbidity-related QALYs University of Adelaide 40
- 41. • ↑probability the reference ICER is <$35,000 per QALY University of Adelaide 41 0.71 0.94 0 0.5 1 $20,000 $30,000 $40,000 Probability Reference ICER: Cost per QALY
- 42. Key assumptions • 2 assumptions underestimate reference ICER • (1) Mortality-related QALY gains assume that averted YLL are lived in same utility as general population (age and gender matched) – Overestimate QALYs lost as YLL more likely in clinical populations with lower HRQoL • Sensitivity analysis using EQ-5D-3L Australian population norms that were 6% higher than our base case values had minimal impact on the reference ICER (reduction of $237) University of Adelaide 42
- 43. Key assumptions • 2 assumptions underestimate reference ICER • (2) Morbidity-related QALY gains assume that the time trend coefficient represents the effects of health spending on pop-level change in HRQoL • Socioeconomic covariates assumed to control for the effects of PHI, individual health spending, non- government spending, social determinants of health University of Adelaide 43
- 44. International comparisons • Accepted ICERs are higher than the estimated opportunity cost of decisions to fund new technologies School of Public Health, University of Adelaide 44 Empirically estimated cost per QALY (£) Current threshold employed (£) Percentage reduction required for threshold to equal the empirically estimated threshold English National Health Service 12,936 20,000 35.3 Spanish National Health Service 18,507 26,409 29.9 Australian Health Care System 16,580 26,615 37.7
- 45. Implications for Australia • F1 drug costs in 2015-16 = $ 4.3b (£2.5b; $176 per capita) • Price reduction of 37.7% could have saved = $1.6b • Or, an additional 57,225 QALYs • Conclusion: To maximise QALYs, we should only fund new technologies with an ICER < $28,033 per QALY University of Adelaide 45
- 46. Use of the reference ICER in practice? • Advisory group • HTA decision-making committees – MSAC & PBAC University of Adelaide 46
- 47. Why might we not use the reference ICER? • Other health-related goals – Reducing inequity in health • Other non-health-related goals – Economic – Political University of Adelaide 47
- 48. Non-health-related goals • Economic – Reduced investment in R&D – Reduced production of pharmaceuticals • Human pharmaceutical and medicinal product manufacturing R&D in Australia = $380m – 8.5% of total Aust. manufacturing ($4.5b) – 2.1% of total Aust. business R&D spending ($18.3b) • Political – Impact on trade deal negotiations – Perceived community response (access) School of Public Health, University of Adelaide 48
- 49. Economic impact • Economic considerations = difficult to quantify • Fiscal multiplier = Δ national income / Δ govt spending • Δ $2 / Δ $1 = multiplier of 2 • Multiplier < 1 = govt spending reduces the size of the economy School of Public Health, University of Adelaide 49
- 50. Fiscal multiplier, example • MS&D from spending in 2000 = $280m to the Australian economy • Average annual cost of PBS subscriptions supplied by MS&D = $347m • Multiplier effect = $280m / $347m = 0.81 = < 1 • Pharmaceutical spending has a lower multiplier effect than other types of health spending University of Adelaide 50
- 51. Trade negotiations • Impact on international trade – Reduction in price paid may reduce bargaining power in trade negotiations • Reference ICER can inform of the net loss in population health – This can provide strong rationale to support change in pricing University of Adelaide 51
- 52. Community response • Community view price reductions unfavourably • (as a result) politicians are more likely to pay high prices University of Adelaide 52
- 53. Herceptin fund in Australia • HTA committees are independent from govt, but there is a political context to decisions made • Herceptin for late stage cancer patients rejected by PBAC based on cost-effectiveness 3 times, late 1990s • In response to patients and patient advocacy groups, Herceptin funded under a special programme independent of the PBS • Media analysis of TV coverage prior to decision: • 54% of all reported statements framed as ‘desperate, sick women in double jeopardy because of callous government/incompetent bureaucracy’ – Due to government financial constraint & mean-spiritedness – Drug industry pricing not mentioned at all University of Adelaide 53
- 54. Herceptin fund in Australia • Conclusions: – Clinicians, patients, their families and patient advocacy groups invoking the rule of rescue increase likelihood of gaining access to expensive healthcare – Rational, criteria-base public health policy will find it hard to resist the rule of rescue imperative (MacKenzie et al. 2008) • But, the cumulative effect of repeatedly applying the rule of rescue will lower the average level of population benefit University of Adelaide 54
- 56. Community perceptions • What do the community think about using the reference ICER – How to elicit informed responses? – Do community understand the trade-offs between new high cost interventions versus additional benefits elsewhere in the healthcare system? University of Adelaide 56
- 57. Community perceptions • Online survey • Informed responses ~5 min video • Research questions/ – Can the concept of opportunity cost be accurately (& relatively easily) communicated to the public – Do informed community members think we should pay more for some new technologies than their opportunity cost? • Pilot responses University of Adelaide 57
- 58. Summary • Reference ICER = $28,033 per QALY – Suggests reductions of almost 40% required to current funding thresholds ~similar to estimates from the UK and Spain • Anticipated barriers to use – Economic • R&D • Manufacturing – Political • Trade negotiations • Popularity of decisions University of Adelaide 58