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INTRODUCTION: Adding pioglitazone or rosiglitazone to existing therapy are alternative treatment options for patients with type 2 diabetes mellitus who have insufficient glycaemic control while receiving the maximal tolerated dose of metformin monotherapy. Our objective was to develop a lifetime model of type 2 diabetes mellitus and its sequelae in order to compare the costs and benefits of pioglitazone versus rosiglitazone in combination with metformin.
METHODS: A decision-analytic model employing a first order Monte Carlo simulation of a Markov process was constructed. The model incorporated surrogate outcome measures from a large randomised controlled trial (RCT) [n = 802] that compared the glycaemic and lipid control of pioglitazone and rosiglitazone monotherapy. These efficacy data were used with a recently validated and peer-reviewed UKPDS (UK Prospective Diabetes Study) algorithm to simulate the progression of these surrogate outcomes to final health outcomes, including quality of life (QOL) and mortality, and to calculate the risks of diabetic complications and death. The model perspective was of the UK NHS and included direct healthcare costs only (pounds, 2004/5 values). Patient outcomes measured in the model included life-expectancy (LE) and QALYs. The base-case analysis was run for 56-year-old male Caucasions with a haemoglobin A(1c) (HbA(1c)) of 7.57% and a body mass index of 33.14 kg/m(2).
RESULTS: Patients treated with pioglitazone experienced a reduction in the total cholesterol to high-density lipoprotein-cholesterol (TC : HDL-C) ratio of 0.34, whereas the TC : HDL-C ratio increased by 0.65 in those receiving rosiglitazone (p < 0.001). The HbA(1c) profile was similar between the treatment groups (p = 0.13), as were other known risk factors for diabetes complications. The lifetime healthcare costs per patient estimated by the model were 9585 pounds for pioglitazone and 10,299 pounds for rosiglitazone. Patients treated with pioglitazone had a discounted LE of 8.83 years versus 8.79 years for those treated with rosiglitazone. Patients treated with pioglitazone also gained additional QALYs (6.8070 vs 6.7686). With improved health outcomes and lower costs, treatment with pioglitazone dominated rosiglitazone treatment. CONCLUSION: Evidence from the only large head-to-head RCT comparing rosiglitazone and pioglitazone suggests that more favourable changes in serum lipid profiles in patients treated with pioglitazone translate into improved health outcomes in terms of reduced morbidity and mortality and greater gains in QOL. In addition, this analysis indicates that treatment with pioglitazone is associated with lower costs than rosiglitazone. Therefore, in the UK, adjunctive pioglitazone may represent a cost-effective treatment choice for patients with type 2 diabetes who have insufficient glycaemic control while receiving the maximal tolerated dose of metformin monotherapy.
Improving health through better nutrition of the population may contribute to enhanced efficiency and sustainability of healthcare systems. A recent expert meeting investigated in detail a number of methodological aspects related to the discipline of nutrition economics. The role of nutrition in health maintenance and in the prevention of non-communicable diseases is now generally recognised. However, the main scope of those seeking to contain healthcare expenditures tends to focus on the management of existing chronic diseases. Identifying additional relevant dimensions to measure and the context of use will become increasingly important in selecting and developing outcome measurements for nutrition interventions. The translation of nutrition-related research data into public health guidance raises the challenging issue of carrying out more pragmatic trials in many areas where these would generate the most useful evidence for health policy decision-making. Nutrition exemplifies all the types of interventions and policy which need evaluating across the health field. There is a need to start actively engaging key stakeholders in order to collect data and to widen health technology assessment approaches for achieving a policy shift from evidence-based medicine to evidence-based decision-making in the field of nutrition.
Citizen preferences surrounding desirable health system characteristics should be considered when undertaking health system reform. The objective of this study was to pilot test a discrete-choice instrument designed to elicit preference weights surrounding health system attributes.
A discrete-choice experiment was designed and administered to two convenience samples (n=50 each) recruited from the UK and Australia. The impact of eight health system attributes representing level of health, equity, responsiveness and healthcare financing on the choice between hypothetical health systems was analysed utilizing mixed logit analysis.
All characteristics affected the likelihood a health system would be preferred, with the exception of the additional tax contribution levels required to finance the system. There were very few missing or inconsistent responses. The direction of preferences was consistent with expectations for both samples; that is, an improvement in attributes describing level of health, equity or responsiveness increased the likelihood that a health system would be preferred.
A number of potential improvements to the preference instrument are suggested. The discrete-choice technique used in this study offers a feasible method for eliciting health system preferences, and its use in a larger-scale study to elicit and compare the preferences of representative population samples is supported.
AIM: To gather evidence to support the implementation of standard six of the National Service Framework for Children, Young People and Maternity Services (Department of Health and Department for Education and Skills 2004), which states that care should be provided as close to home as possible.
METHODS: A mixed methods study comprising of a systematic review, a national survey of provision of care closer to home (CCTH), four in-depth, qualitative case studies and a cost analysis.
FINDINGS: The systematic review suggests that CCTH is no less clinically effective than hospital care. Services identified by the survey fall into three distinct models of provision. Case study data show that families preferred CCTH, but staff face difficulties at organisational and practice levels. Cost analysis suggests there can be cost savings with CCTH, but several factors influence these.
CONCLUSION: CCTH may be an effective and feasible option for children and young people who are ill.
AIMS: To estimate the current and future economic burdens of Type 1 and Type 2 diabetes in the UK.
METHODS: A top-down approach was used to estimate costs for 2010/2011 from aggregated data sets and literature. Prevalence and population data were used to project costs for 2035/2036. Direct health costs were estimated from data on diagnosis, lifestyle interventions, ongoing treatment and management, and complications. Indirect costs were estimated from data on mortality, sickness, presenteeism (potential loss of productivity among people who remain in work) and informal care.
RESULTS: Diabetes cost approximately £23.7bn in the UK in 2010/2011: £9.8bn in direct costs (£1bn for Type 1 diabetes and £8.8bn for Type 2 diabetes) and £13.9bn in indirect costs (£0.9bn and £13bn). In real terms, the 2035/2036 cost is estimated at £39.8bn: £16.9bn in direct costs (£1.8bn for Type 1 diabetes and £15.1bn for Type 2 diabetes) and £22.9bn in indirect costs (£2.4bn and £20.5bn). Sensitivity analysis applied to the direct costs produced a range of costs: between £7.9bn and £11.7bn in 2010/2011 and between £13.8bn and £20bn in 2035/2036. Diabetes currently accounts for approximately 10% of the total health resource expenditure and is projected to account for around 17% in 2035/2036.
CONCLUSIONS: Type 1 and Type 2 diabetes are prominent diseases in the UK and are a significant economic burden. Data differentiating between the costs of Type 1 and Type 2 diabetes are sparse. Complications related to the diseases account for a substantial proportion of the direct health costs. As prevalence increases, the cost of treating complications will grow if current care regimes are maintained.
OBJECTIVE: In the Medical Research Council Myeloma IX Study (MMIX), zoledronic acid (ZOL) 4 mg 3-4/week reduced the incidence of skeletal-related events (SREs), increased progression free survival (PFS), and prolonged overall survival (OS), compared with clodronic acid (CLO) 1600 mg daily, in 1970 patients with newly-diagnosed multiple myeloma (MM).
METHODS: An economic model was used to project PFS, OS, the incidence of SREs and adverse events and expected lifetime healthcare costs for patients with newly-diagnosed MM who are alternatively assumed to receive ZOL or CLO. The incremental cost-effectiveness ratio [ICER] of ZOL vs CLO was calculated as the ratio of the difference in cost to the difference in quality-adjusted life years (QALYs). Model inputs were based on results of MMIX and published sources.
RESULTS: Compared with CLO, treatment with ZOL increases QALYs by 0.30 at an additional cost of £1653, yielding an ICER of £5443 per QALY gained. If the threshold ICER is £20,000 per QALY, the estimated probability that ZOL is cost-effective is 90%.
LIMITATIONS: The main limitation of this study is the lack of data on the effects of zoledronic acid on survival beyond the end of follow-up in the MMIX trial. However, cost-effectiveness was favourable even under the highly conservative scenario in which the timeframe of the model was limited to 5 years.
CONCLUSION: Compared with clodronic acid, zoledronic acid represents a cost-effective treatment alternative in patients with multiple myeloma.
