Alan Brennan

Estimated effect of alcohol pricing policies on health and health economic outcomes in England: an epidemiological model

BACKGROUND Although pricing policies for alcohol are known to be effective, little is known about how specific interventions affect health-care costs and health-related quality-of-life outcomes for different types of drinkers. We assessed effects of alcohol pricing and promotion policy options in various population subgroups. METHODS We built an epidemiological mathematical model to appraise 18 pricing policies, with English data from the Expenditure and Food Survey and the General Household Survey for average and peak alcohol consumption. We used results from econometric analyses (256 own-price and cross-price elasticity estimates) to estimate effects of policies on alcohol consumption. We applied risk functions from systemic reviews and meta-analyses, or derived from attributable fractions, to model the effect of consumption changes on mortality and disease prevalence for 47 illnesses. FINDINGS General price increases were effective for reduction of consumption, health-care costs, and health-related quality of life losses in all population subgroups. Minimum pricing policies can maintain this level of effectiveness for harmful drinkers while reducing effects on consumer spending for moderate drinkers. Total bans of supermarket and off-license discounting are effective but banning only large discounts has little effect. Young adult drinkers aged 18-24 years are especially affected by policies that raise prices in pubs and bars. INTERPRETATION Minimum pricing policies and discounting restrictions might warrant further consideration because both strategies are estimated to reduce alcohol consumption, and related health harms and costs, with drinker spending increases targeting those who incur most harm. FUNDING Policy Research Programme, UK Department of Health.

Delivering the diabetes education and self management for ongoing and newly diagnosed (DESMOND) programme for people with newly diagnosed type 2 diabetes: cost effectiveness analysis

Objectives To assess the long term clinical and cost effectiveness of the diabetes education and self management for ongoing and newly diagnosed (DESMOND) intervention compared with usual care in people with newly diagnosed type 2 diabetes. Design We undertook a cost-utility analysis that used data from a 12 month, multicentre, cluster randomised controlled trial and, using the Sheffield type 2 diabetes model, modelled long term outcomes in terms of use of therapies, incidence of complications, mortality, and associated effect on costs and health related quality of life. A further cost-utility analysis was also conducted using current “real world” costs of delivering the intervention estimated for a hypothetical primary care trust. Setting Primary care trusts in the United Kingdom. Participants Patients with newly diagnosed type 2 diabetes. Intervention A six hour structured group education programme delivered in the community by two professional healthcare educators. Main outcome measures Incremental costs and quality adjusted life years (QALYs) gained. Results On the basis of the data in the trial, the estimated mean incremental lifetime cost per person receiving the DESMOND intervention is £209 (95% confidence interval −£704 to £1137; €251, −€844 to €1363;

Modeling Using Discrete Event Simulation A Report of the ISPOR-SMDM Modeling Good Research Practices Task Force–4

326, −

Policy options for alcohol price regulation: the importance of modelling population heterogeneity.

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Effects of minimum unit pricing for alcohol on different income and socioeconomic groups: a modelling study

1773), the incremental gain in QALYs per person is 0.0392 (−0.0813 to 0.1786), and the mean incremental cost per QALY is £5387. Using “real world” intervention costs, the lifetime incremental cost of the DESMOND intervention is £82 (−£831 to £1010) and the mean incremental cost per QALY gained is £2092. A probabilistic sensitivity analysis indicated that the likelihood that the DESMOND programme is cost effective at a threshold of £20 000 per QALY is 66% using trial based intervention costs and 70% using “real world” costs. Results from a one way sensitivity analysis suggest that the DESMOND intervention is cost effective even under more modest assumptions that include the effects of the intervention being lost after one year. Conclusion Our results suggest that the DESMOND intervention is likely to be cost effective compared with usual care, especially with respect to the real world cost of the intervention to primary care trusts, with reductions in weight and smoking being the main benefits delivered.

Should patients have a greater role in valuing health states

Discrete event simulation (DES) is a form of computer-based modeling that provides an intuitive and flexible approach to representing complex systems. It has been used in a wide range of health care applications. Most early applications involved analyses of systems with constrained resources, where the general aim was to improve the organization of delivered services. More recently, DES has increasingly been applied to evaluate specific technologies in the context of health technology assessment. The aim of this article was to provide consensus-based guidelines on the application of DES in a health care setting, covering the range of issues to which DES can be applied. The article works through the different stages of the modeling process: structural development, parameter estimation, model implementation, model analysis, and representation and reporting. For each stage, a brief description is provided, followed by consideration of issues that are of particular relevance to the application of DES in a health care setting. Each section contains a number of best practice recommendations that were iterated among the authors, as well as among the wider modeling task force.

Modelling in Health Economic Evaluation What is its Place? What is its Value?

Context and aims Internationally, the repertoire of alcohol pricing policies has expanded to include targeted taxation, inflation-linked taxation, taxation based on alcohol-by-volume (ABV), minimum pricing policies (general or targeted), bans of below-cost selling and restricting price-based promotions. Policy makers clearly need to consider how options compare in reducing harms at the population level, but are also required to demonstrate proportionality of their actions, which necessitates a detailed understanding of policy effects on different population subgroups. This paper presents selected findings from a policy appraisal for the UK government and discusses the importance of accounting for population heterogeneity in such analyses. Method We have built a causal, deterministic, epidemiological model which takes account of differential preferences by population subgroups defined by age, gender and level of drinking (moderate, hazardous, harmful). We consider purchasing preferences in terms of the types and volumes of alcoholic beverages, prices paid and the balance between bars, clubs and restaurants as opposed to supermarkets and off-licenses. Results Age, sex and level of drinking fundamentally affect beverage preferences, drinking location, prices paid, price sensitivity and tendency to substitute for other beverage types. Pricing policies vary in their impact on different product types, price points and venues, thus having distinctly different effects on subgroups. Because population subgroups also have substantially different risk profiles for harms, policies are differentially effective in reducing health, crime, work-place absence and unemployment harms. Conclusion Policy appraisals must account for population heterogeneity and complexity if resulting interventions are to be well considered, proportionate, effective and cost-effective.

Calculating Partial Expected Value of Perfect Information via Monte Carlo Sampling Algorithms

Summary Background Several countries are considering a minimum price policy for alcohol, but concerns exist about the potential effects on drinkers with low incomes. We aimed to assess the effect of a £0·45 minimum unit price (1 unit is 8 g/10 mL ethanol) in England across the income and socioeconomic distributions. Methods We used the Sheffield Alcohol Policy Model (SAPM) version 2.6, a causal, deterministic, epidemiological model, to assess effects of a minimum unit price policy. SAPM accounts for alcohol purchasing and consumption preferences for population subgroups including income and socioeconomic groups. Purchasing preferences are regarded as the types and volumes of alcohol beverages, prices paid, and the balance between on-trade (eg, bars) and off-trade (eg, shops). We estimated price elasticities from 9 years of survey data and did sensitivity analyses with alternative elasticities. We assessed effects of the policy on moderate, hazardous, and harmful drinkers, split into three socioeconomic groups (living in routine or manual households, intermediate households, and managerial or professional households). We examined policy effects on alcohol consumption, spending, rates of alcohol-related health harm, and opportunity costs associated with that harm. Rates of harm and costs were estimated for a 10 year period after policy implementation. We adjusted baseline rates of mortality and morbidity to account for differential risk between socioeconomic groups. Findings Overall, a minimum unit price of £0·45 led to an immediate reduction in consumption of 1·6% (−11·7 units per drinker per year) in our model. Moderate drinkers were least affected in terms of consumption (−3·8 units per drinker per year for the lowest income quintile vs 0·8 units increase for the highest income quintile) and spending (increase in spending of £0·04 vs £1·86 per year). The greatest behavioural changes occurred in harmful drinkers (change in consumption of −3·7% or −138·2 units per drinker per year, with a decrease in spending of £4·01), especially in the lowest income quintile (−7·6% or −299·8 units per drinker per year, with a decrease in spending of £34·63) compared with the highest income quintile (−1·0% or −34·3 units, with an increase in spending of £16·35). Estimated health benefits from the policy were also unequally distributed. Individuals in the lowest socioeconomic group (living in routine or manual worker households and comprising 41·7% of the sample population) would accrue 81·8% of reductions in premature deaths and 87·1% of gains in terms of quality-adjusted life-years. Interpretation Irrespective of income, moderate drinkers were little affected by a minimum unit price of £0·45 in our model, with the greatest effects noted for harmful drinkers. Because harmful drinkers on low incomes purchase more alcohol at less than the minimum unit price threshold compared with other groups, they would be affected most by this policy. Large reductions in consumption in this group would however coincide with substantial health gains in terms of morbidity and mortality related to reduced alcohol consumption. Funding UK Medical Research Council and Economic and Social Research Council (grant G1000043).

Modeling Using Discrete Event Simulation

Currently, health state values are usually obtained from members of the general public trying to imagine what the state would be like rather than by patients who are actually in the various states of health. Valuations of a health state by patients tend to vary from those of the general population, and this seems to be due to a range of factors including errors in the descriptive system, adaptation to the state and changes in internal standards. The question of whose values are used in cost-effectiveness analysis is ultimately a normative one, but the decision should be informed by evidence on the reasons for the differences. There is a case for obtaining better informed general population preferences by providing more information on what it is like for patients (including the process of adaptation).

An Overview of Economic Evaluations for Drugs Used in Rheumatoid Arthritis

This paper itemises the current and developing roles of modelling in health economic evaluation and discusses its value in each role.We begin by noting the emptiness of the dichotomy that some commentators have sought to create between modelling and controlled trials as mechanisms for informing decisions. Both are necessary parts of the armoury. Recent literature discussions are examined and the accelerating prevalence of modelling is reported.The identified roles include: extrapolating outcomes to the longer term; adjusting for prognostic factors in trials; translating from intermediate to final outcomes; extending analysis to the relevant comparators; generalising from specific trial populations to the full target group for an intervention and to other settings and countries; systematic sensitivity analyses; and the use of modelling for the design and prioritisation of future trials.Roles are illustrated with 20 recent examples, mostly from within our own work analysing new or contentious interventions for the Trent Development and Evaluation Committee, which is planned to be incorporated into the UK National Institute for Clinical Excellence (NICE). Each role discussed has been essential at some point in this policy-making forum.Finally, the importance of quality assurance, critical review and validity testing is reiterated and there are some observations on processes to ensure probity and quality.