Does the National Institute for Health and Clinical Excellence take account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services? A binary choice experiment

Background: NICE is an independent organisation responsible for providing national guidance on the promotion of good health and the prevention and treatment of ill health in England and Wales. One of NICE’s main roles is to produce national guidance on the use of health technologies within the NHS. Despite the Institute’s recent efforts to clarify the way in which its Appraisal Committees reach their recommendations concerning the use of health technologies, there remains ambiguity about how cost-effectiveness evidence is interpreted alongside other considerations such as the degree of clinical need within the patient population, and the degree of uncertainty surrounding cost-effectiveness estimates. Objective: To explore whether the NICE takes account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services. Methods: A binary choice experiment was undertaken using NICE’s three Appraisal Committees. The experiment included five attributes: (1) Incremental cost-effectiveness (2) Degree of economic uncertainty (3) Age of the target population (4) Baseline health-related quality of life (5) Availability of other therapies A choice questionnaire detailing 18 scenarios was administered to NICE’s Appraisal Committees. For each scenario, respondents were asked to indicate whether they would recommend the intervention under consideration or not. The stated preference data obtained from respondents were analysed using a random effects logit regression model. Results: A response rate of 46% was obtained from the Appraisal Committees. The regression model suggests that increases in cost-effectiveness, economic uncertainty, and the availability of other therapies are associated with statistically significant reductions in the odds of adoption (p<0.05). The transition from a very low to a comparatively high level of health-related quality of life is also associated with a statistically significant reduction in the odds of a positive recommendation. Smaller changes in health-related quality of life, and the age of the target population are not associated with a statistically significant reduction in the odds of a positive recommendation. Analysis of revealed preference data indicates that the model is capable of distinguishing between those technologies which the Appraisal Committees would be highly likely to recommend, and those technologies which appear to be less attractive, although further external validation is warranted. Conclusion: The modelling suggests that cost-effectiveness, uncertainty and certain equity concerns influence the NICE Appraisal Committees’ recommendations on the use of health technologies. The modelling results appear to support Rawlins and Culyer’s notion of a probabilistic cost-effectiveness threshold approach; the "mythical" £30,000 per QALY gained threshold assumed within the literature is not supported by this stated preference modelling analysis

Does the National Institute for Health and Clinical Excellence take account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services? A binary choice experiment

Background NICE is an independent organisation responsible for providing national guidance on the promotion of good health and the prevention and treatment of ill health in England and Wales. One of NICE’s main roles is to produce national guidance on the use of health technologies within the NHS. Despite the Institute’s recent efforts to clarify the way in which its Appraisal Committees reach their recommendations concerning the use of health technologies, there remains ambiguity about how cost-effectiveness evidence is interpreted alongside other considerations such as the degree of clinical need within the patient population, and the degree of uncertainty surrounding cost-effectiveness estimates. Objective To explore whether the NICE takes account of factors such as uncertainty and equity as well as incremental cost-effectiveness in commissioning health care services. Methods A binary choice experiment was undertaken using NICE’s three Appraisal Committees. The experiment included five attributes: (1) Incremental cost-effectiveness (2) Degree of economic uncertainty (3) Age of the target population (4) Baseline health-related quality of life (5) Availability of other therapies A choice questionnaire detailing 18 scenarios was administered to NICE’s Appraisal Committees. For each scenario, respondents were asked to indicate whether they would recommend the intervention under consideration or not. The stated preference data obtained from respondents were analysed using a random effects logit regression model. Results A response rate of 46% was obtained from the Appraisal Committees. The regression model suggests that increases in cost-effectiveness, economic uncertainty, and the availability of other therapies are associated with statistically significant reductions in the odds of adoption (puncertainty; equity; cost-effectiveness; public health

Modelling the cost effectiveness of interferon beta and glatiramer acetate in the management of multiple sclerosis

OBJECTIVE: To evaluate the cost effectiveness of four disease modifying treatments (interferon betas and glatiramer acetate) for relapsing remitting and secondary progressive multiple sclerosis in the United Kingdom. DESIGN: Modelling cost effectiveness. SETTING: UK NHS. PARTICIPANTS: Patients with relapsing remitting multiple sclerosis and secondary progressive multiple sclerosis. MAIN OUTCOME MEASURES: Cost per quality adjusted life year gained. RESULTS: The base case cost per quality adjusted life year gained by using any of the four treatments ranged from £42 000 ($66 469; 61 630) to £98 000 based on efficacy information in the public domain. Uncertainty analysis suggests that the probability of any of these treatments having a cost effectiveness better than £20 000 at 20 years is below 20%. The key determinants of cost effectiveness were the time horizon, the progression of patients after stopping treatment, differential discount rates, and the price of the treatments. CONCLUSIONS: Cost effectiveness varied markedly between the interventions. Uncertainty around point estimates was substantial. This uncertainty could be reduced by conducting research on the true magnitude of the effect of these drugs, the progression of patients after stopping treatment, the costs of care, and the quality of life of the patients. Price was the key modifiable determinant of the cost effectiveness of these treatments

Choice and judgement in developing models for health technology assessment; a qualitative study

Introduction: The role of models in supporting health policy decisions is reliant on model credibility. Credibility is fundamentally determined by the choices and judgements that people make in the process of developing a model. However, the method of uncovering choices and making judgements in model development is largely unreported and is not addressed by modelling methods guidance. Methods: This qualitative study was part of a project examining errors in health technology assessment models. In-depth interviews with academic and commercial modellers were used to obtain descriptions of the model development process. Data were analysed using framework analysis and interpreted in the context of the methodological literature. Results: The activities involved in developing models were characterised according to the themes; understanding the decision problem, conceptual modelling, model implementation, model checking, and engaging with the decision maker. Finding and using evidence was frequently mentioned across these themes. There was marked variation between practitioners in the extent to which conceptual modelling was recognised as an activity distinct from model implementation. Discussion: Methodological approaches to addressing model credibility described in the wider modelling literature highlight the necessity to disentangle the conceptual modelling and implementation activities. Whilst interviewees talked of judgements and choice making throughout model development, discussion indicated that these were based upon skills and experience with no discussion of formal approaches. Methods are required that provide for a systematic approach to uncovering choices, to generating a shared view of consensus and divergence, and for making judgements and choices in model development

Proceed with caution: an economic perspective on the UK's value based pricing proposals

The shift from the Pharmaceutical Pricing Regulation Scheme to Value Based Pricing (VBP) is an important change in the way that medicines will be priced, and consequently, reimbursed in the United Kingdom. Whilst the opportunity to purchase new medicines based on value to society is one that should be welcomed, we should proceed with caution. We highlight ten issues that should be considered relating to innovation, the role and meaning of funding threshold and the adjustments to reflect burden of illness, therapeutic innovation and improvement and wider societal factors. Most importantly, the assessment of value should continue to be based on the characteristics of the displaced activities (e.g. the health produced). To a large extent, all that is changing under VBP are the characteristics being considered; weighted health rather than unweighted health. In addition, we should not totally abandon a cost-utility framework for appraisal just because its current formulation does not match the wider perspective now desired by government

Evaluation of the cost-effectiveness of services for Schizophrenia in the UK across the entire care pathway in a single whole-disease model

Importance The existing economic models for schizophrenia often have 3 limitations; namely, they do not cover nonpharmacologic interventions, they report inconsistent conclusions for antipsychotics, and they have poor methodologic quality. Objectives To develop a whole-disease model for schizophrenia and use it to inform resource allocation decisions across the entire care pathway for schizophrenia in the UK. Design, Setting, and Participants This decision analytical model used a whole-disease model to simulate the entire disease and treatment pathway among a simulated cohort of 200 000 individuals at clinical high risk of psychoses or with a diagnosis of psychosis or schizophrenia being treated in primary, secondary, and tertiary care in the UK. Data were collected March 2016 to December 2018 and analyzed December 2018 to April 2019. Exposures The whole-disease model used discrete event simulation; its structure and input data were informed by published literature and expert opinion. Analyses were conducted from the perspective of the National Health Service and Personal Social Services over a lifetime horizon. Key interventions assessed included cognitive behavioral therapy, antipsychotic medication, family intervention, inpatient care, and crisis resolution and home treatment team. Main Outcomes and Measures Life-time costs and quality-adjusted life-years. Results In the simulated cohort of 200 000 individuals (mean [SD] age, 23.5 [5.1] years; 120 800 [60.4%] men), 66 400 (33.2%) were not at risk of psychosis, 69 800 (34.9%) were at clinical high risk of psychosis, and 63 800 (31.9%) had psychosis. The results of the whole-disease model suggest the following interventions are likely to be cost-effective at a willingness-to-pay threshold of £20 000 ($25 552) per quality-adjusted life-year: practice as usual plus cognitive behavioral therapy for individuals at clinical high risk of psychosis (probability vs practice as usual alone, 0.96); a mix of hospital admission and crisis resolution and home treatment team for individuals with acute psychosis (probability vs hospital admission alone, 0.99); amisulpride (probability vs all other antipsychotics, 0.39), risperidone (probability vs all other antipsychotics, 0.30), or olanzapine (probability vs all other antipsychotics, 0.17) combined with family intervention for individuals with first-episode psychosis (probability vs family intervention or medication alone, 0.58); and clozapine for individuals with treatment-resistant schizophrenia (probability vs other medications, 0.81). Conclusions and Relevance The results of this study suggest that the current schizophrenia service configuration is not optimal. Cost savings and/or additional quality-adjusted life-years may be gained by replacing current interventions with more cost-effective interventions