Application of EQ-5D in Reimbursement Decision Making: The Case of NICE


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Application of EQ-5D in Reimbursement Decision Making: The Case of NICE

  1. 1. The Application of EQ-5D inReimbursement Decision Making – The Case of NICE Professor Nancy J. Devlin Director of Research, Office of Health Economics Chair, EuroQol Group Executive CommitteeValuing Health Outcomes for Healthcare Decision Making Using the EQ-5D: A Symposium for Policy Makers and Researchers in Asia Singapore 22 March 2013
  2. 2. Contents1. Introduction: HTA, value for money, and outcomes measurement2. NICE Health Technology Appraisal: purpose & process3. The relationship between cost effectiveness and NICE decisions4. The role of EQ-5D in NICE decision making5. Collecting and analysing EQ-5D data to inform HTA6. Utility weighting EQ-5D profiles – the role of value sets7. What if EQ-5D data are not available?8. Is EQ-5D always appropriate?9. Concluding remarks
  3. 3. 1. HTA, value for money, and outcomes measurement• Health care budgets are limited• Increasing demand for health care, e.g. from – Aging populations – Rising expectations about health and health care – Improvements in health care technology• Most new technologies improve health (length/quality of life), but also increase costs• Reimbursing such technologies has an opportunity cost: the benefits possible from the next best opportunity foregone
  4. 4. • How can we judge whether new technologies are good value for money?• Need to be able to compare health gained with health foregone• Aim is to achieve an allocation of budgets that maximises health• Cost effectiveness analysis provides a means of comparing value for money• This requires a standardised measure of health outcomes, e.g. the QALY• Which in turn requires a standardised, generic means of measuring patients‘ quality of life, e.g. EQ-5D
  5. 5. 2. NICE HTA: Purpose & Process• Purpose: ―to offer health professionals guidance on the use of technologies, based on a rigorous review of the available evidence‖• In doing so, it takes the following six matters into account: – The clinical needs of patients – NHS priorities – The broad balance between benefits and costs, incorporating both clinical and cost effectiveness – Potential impact on other NHS resources – Encouragement of innovation – Guidance from ministers on the resources available
  6. 6. 3. Cost Effectiveness and NICE Decisions – ―[NICE] should, generally, accept as cost effective those interventions with an incremental cost-effectiveness ratio of less than £20,000 per QALY and that there should be increasingly strong reasons for accepting as cost effective interventions with an incremental cost- effectiveness ratio of over £30,000 per QALY.‖
  7. 7. Modelling NICE DecisionsAt average levels for all covariates, a decision would have a50% chance of rejection if its ICER were £45,118/QALY Source: Dakin, Devlin, Rice, Parkin, O’Neill, Feng (2013) The influence of cost effectiveness and other factors on NICE decisions. (forthcoming)
  8. 8. 4. Role of EQ-5D in NICE’s HTA Process• NICE requests that its HTA include an analysis of incremental cost effectiveness• NICE methods guide (2008) states a clear and strong preference for a single instrument: EQ-5D• But acknowledges that – EQ-5D data not always available – EQ-5D may not always be the appropriate measure
  9. 9. 5. Collecting and Analysing EQ-5D Data to Inform HTA• EQ-5D can be included alongside disease specific PROs in clinical trials and observational studies – E.g. baseline; 4 weeks; 8 weeks; 12 weeks – More frequent data collection also feasible, e.g. daily patient diary – Which is appropriate will depend on the nature of the disease and intervention• Various modes of data collection possible, e.g. paper and pencil; web-based; PDA; telephone• Data can be used to test for statistically significant improvements in outcomes compared to placebo and/or relevant comparators• Results used to populate health economics models
  10. 10. Daily Reports of EQ-VAS for Multiple Sclerosis PatientsSource: Parkin, et al. (2004) Use of a VAS in a daily patient diary. Soc Sci Med 59:351-360.
  11. 11. 6. Utility Weighting EQ-5D Profiles – the Role of Value Sets• Patients self-report their health on EQ-5D• For the purposes of HTA, and estimating QALYs, patients‘ EQ-5D ‗profiles‘ are summarised by a single number, on a scale anchored at 1 (full health) and 0 (dead)• These QoL weights/‘values‘ come from ‗value sets‘, based on preferences of the general public• ‗Stated preferences‘: questions (eg. TTO, DCE, SG) to indicate how good or bad health states are from the perspective of members of the general public (imagining living in EQ-D states)
  12. 12. Applying Value Sets to EQ-5D Profile Data Measuring health on ageneric HR-QoL instrument: the EQ-5D
  13. 13. York ‘MVH’ Model, Based on TTO Valuations of EQ-5D Health StatesAttribute 12122 32111 12233Constant -0.03 -0.03 -0.03 -0.03Mobility level 2 -0.066Mobility level 3 -0.271 -0.271Self care level 2 -0.029 -0.029 -0.029 -0.029Self care level 3 -0.097Usual activities level 2 -0.127 -0.127Usual activities level 3 -0.224Pain & discomfort level 2 -0.144 -0.144Pain & discomfort level 3 -0.376 -0.376Anxiety & depression level 2 -0.114 -0.114Anxiety & depression level 3 -0.259 -0.259Any level 3 -0.305 -0.305 -0.305 Sum of utility loss -.317 -0.635 -1.126 Value of health state 0.683 0.365 -0.126Source: Dolan (1996) Medical Care
  14. 14. The Role of Values in Statistical Analysis• Index values within a data set are the product of both the data being analysed (the profile) and externally provided data (the weights)• Health state index data are therefore the result of information both on the people whose health has been measured and on those whose values have been measured• Parkin, Rice and Devlin (2010): weights introduce an exogenous source of variance which affects statistical inference using the index data• Implication: important to use appropriate, local value sets in HTA
  15. 15. Example from a Recent Clinical Trial of Treatments for OABSource: Pavesi, Devlin, Hakimi, Herdman, Nazir, Odeyemi. (2013) Understanding the effects on HR-QoL of treatment foroveractive bladder: a detailed analysis of EQ-5D clinical trial data for mirabegron. (forthcoming).
  16. 16. 7. What if EQ-5D Data Are Not Available?• Mapping from a disease specific PRO to EQ-5D is possible.• Various methods available (direct vs. indirect)• NICE DSU recommendations on mapping• Mapping is subject to some important challenges and limitations…“Where relevant EQ-5D data are not available, then another solution would be tomap from another measure of HRQL or disease severity that has been used inrelevant studies and to predict EQ-5D responses from statistical mappingfunctions. These can be estimated from other data sets containing bothinstruments. This strategy is accepted by NICE in the absence of EQ-5Ddata, but it is always second best to the direct use of EQ-5D and may come witha penalty of increased uncertainty.”
  17. 17. 8. Is EQ-5D Always Appropriate?• EQ-5D shown to be a reliable and sensitive measure of patient reported outcomes in many disease areas—but not all• EQ-5D may not always be the appropriate measure: lacking sensitivity; ‗missing‘ descriptive items• For a recent review, see NICE DSU report on EQ-5D
  18. 18. Evidence on EQ-5D: Some Examples Hearing Schizophrenia Bipolar disorder Vision Depression and anxiety Some cancers Skin Personality disorder
  19. 19. What Can Be Done when EQ-5D Is Shown Not to Be Appropriate?1. Generic preference-based measure (e.g. SF-6D or HUI3)—but concerns about comparability between generic measures2. Condition specific preference-based measure—more concerns about comparability between QALYs generated by different instruments (e.g. for dementia, cancer, asthma and so on) due to focusing effects, comorbidities, side-effects Develop extra ‘bolt on’ dimensions for EQ-5D?
  20. 20. What Are the Issues for Bolt-On Development?1. Determine candidate dimensions2. Develop labels and levels3. Psychometric testing4. Test impact on health state values5. Test impact on the form of the preference function for whole EQ-5D – are bolt-ons simply additive?6. Estimating value sets/functions with new bolt-ons
  21. 21. 9. Concluding Remarks• From 2014 in UK: Value Based Pricing (VBP) – Changing (expanded) role for NICE – QALYs (and EQ-5D) highly likely to be central to assessments of the value of new technologies in VBP• Plans to introduce VBP have further highlighted questions about what the ‗cost effectiveness threshold‘ should be. – Debate over what methods best identify the opportunity cost• To ensure budgets used efficiently (produce as much health as possible) important to look at value for money of both new and old technologies• Measurement of outcomes in ‗real world‘ settings will become increasingly important
  22. 22. For additional information, please contact Prof Nancy Devlin atndevlin@ohe.orgTo keep up with the latest news and research, subscribe to our blog, OHE News.Follow us on Twitter @OHENews, LinkedIn and SlideShare.Office of Health Economics (OHE)Southside, 7th Floor105 Victoria StreetLondon SW1E 6QTUnited Kingdom+44 20 7747 8850www.ohe.orgOHE’s publications may be downloaded free of charge by registered users of its website.©2013 OHE