Bridging the gap between methods research and the needs of policy makers: A review of the research priorities of the National Institute for Health and Clinical Excellence

Objectives: The aim of this study was to establish a list of priority topics for methods research to support decision making at the National Institute for Health and Clinical Excellence (NICE). Methods: Potential priorities for methods research topics were identified through a focused literature review, interviews, an email survey, a workshop and a Web-based feedback exercise. Participants were members of the NICE secretariat and its advisory bodies, representatives from academia, industry, and other organizations working closely with NICE. The Web exercise was open to anyone to complete but publicized among the above groups. Results: A list of potential topics was collated. Priorities for further research differed according to the type of respondent and the extent to which they work directly with NICE. Priorities emerging from the group closest to NICE included: methodology for indirect and mixed treatment comparisons; synthesis of qualitative evidence; research relating to the use of quality-adjusted life-years (QALYs) in decision making; methods and empirical research for establishing the cost-effectiveness threshold; and determining how data on the uncertainty of effectiveness and cost-effectiveness data should be taken into account in the decision-making process. Priorities emerging from the broadest group of respondents (through the Web exercise) included: methods for extrapolating beyond evidence observed in trials, methods for capturing benefits not included in the QALY and methods to assess when technologies should be recommended in the context of further evidence gathering. Conclusions: Consideration needs to be given to the needs of those who use the outputs of research for decision making when determining priorities for future methods research.NIHR Medical Research Council

Health state utility values for diabetic retinopathy: protocol for a systematic review and meta-analysis

Background People with diabetic retinopathy tend to have lower levels of health-related quality of life than individuals with no retinopathy. Strategies for screening and treatment have been shown to be cost-effective. In order to reduce the bias in cost-effectiveness estimates, systematic reviews of health state utility values (HSUVs) are crucial for health technology assessment and the development of decision analytic models. A review and synthesis of HSUVs for the different stages of disease progression in diabetic retinopathy has not previously been conducted. Methods/Design We will conduct a systematic review of the available literature that reports HSUVs for people with diabetic retinopathy, in correspondence with current stage of disease progression and/or visual acuity. We will search Medline, EMBASE, Web of Science, Cost-Effectiveness Analysis Registry, Centre for Reviews and Dissemination Database, and EconLit to identify relevant English-language articles. Data will subsequently be synthesized using linear mixed effects modeling meta-regression. Additionally, reported disease severity classifications will be mapped to a four-level grading scale for diabetic retinopathy. Discussion The systematic review and meta-analysis will provide important evidence for future model-based economic evaluations of technologies for diabetic retinopathy. The meta-regression will enable the estimation of utility values at different disease stages for patients with particular characteristics and will also highlight where the design of the study and HSUV instrument have influenced the reported utility values. We believe this protocol to be the first of its kind to be published

Does intensive management improve remission rates in patients with intermediate rheumatoid arthritis? (the TITRATE trial): study protocol for a randomised controlled trial.

BACKGROUND: Uncontrolled active rheumatoid arthritis can lead to increasing disability and reduced quality of life over time. 'Treating to target' has been shown to be effective in active established disease and also in early disease. However, there is a lack of nationally agreed treatment protocols for patients with established rheumatoid arthritis who have intermediate disease activity. This trial is designed to investigate whether intensive management of disease leads to a greater number of remissions at 12 months. Levels of disability and quality of life, and acceptability and cost-effectiveness of the intervention will also be examined. METHODS: The trial is a 12-month, pragmatic, randomised, open-label, two-arm, parallel-group, multicentre trial undertaken at specialist rheumatology centres across England. Three hundred and ninety-eight patients with established rheumatoid arthritis will be recruited. They will currently have intermediate disease activity (disease activity score for 28 joints assessed using an erythrocyte sedimentation rate of 3.2 to 5.1 with at least three active joints) and will be taking at least one disease-modifying anti-rheumatic drug. Participants will be randomly selected to receive intensive management or standard care. Intensive management will involve monthly clinical reviews with a specialist health practitioner, where drug treatment will be optimised and an individualised treatment support programme delivered based on several principles of motivational interviewing to address identified problem areas, such as pain, fatigue and adherence. Standard care will follow standard local pathways and will be in line with current English guidelines from the National Institute for Health and Clinical Excellence. Patients will be assessed initially and at 6 and 12 months through self-completed questionnaires and clinical evaluation. DISCUSSION: The trial will establish whether the known benefits of intensive treatment strategies in active rheumatoid arthritis are also seen in patients with established rheumatoid arthritis who have moderately active disease. It will evaluate both the clinical and cost-effectiveness of intensive treatment. TRIAL REGISTRATION: Current Controlled Trials, ID: ISRCTN70160382 . Registered on 16 January 2014.MRC Funding: MC_UP_1302/3 NIHR Funding: RP-PG-0610-1006

Developing a utility index for the Aberrant Behavior Checklist (ABC-C) for fragile X syndrome

Purpose This study aimed to develop a utility index (the ABC-UI) from the Aberrant Behavior Checklist-Community (ABC-C), for use in quantifying the benefit of emerging treatments for fragile X syndrome (FXS). Methods The ABC-C is a proxy-completed assessment of behaviour and is a widely used measure in FXS. A subset of ABC-C items across seven dimensions was identified to include in health state descriptions. This item reduction process was based on item performance, factor analysis and Rasch analysis performed on an observational study dataset, and consultation with five clinical experts and a methodological expert. Dimensions were combined into health states using an orthogonal design and valued using time trade-off (TTO), with lead-time TTO methods used where TTO indicated a state valued as worse than dead. Preference weights were estimated using mean, individual level, ordinary least squares and random-effects maximum likelihood estimation [RE (MLE)] regression models. Results A representative sample of the UK general public (n = 349; mean age 35.8 years, 58.2 % female) each valued 12 health states. Mean observed values ranged from 0.92 to 0.16 for best to worst health states. The RE (MLE) model performed best based on number of significant coefficients and mean absolute error of 0.018. Mean utilities predicted by the model covered a similar range to that observed. Conclusions The ABC-UI estimates a wide range of utilities from patient-level FXS ABC-C data, allowing estimation of FXS health-related quality of life impact for economic evaluation from an established FXS clinical trial instrument

Innovation in health economic modelling of service improvements for longer-term depression: demonstration in a local health community

Background The purpose of the analysis was to develop a health economic model to estimate the costs and health benefits of alternative National Health Service (NHS) service configurations for people with longer-term depression. Method Modelling methods were used to develop a conceptual and health economic model of the current configuration of services in Sheffield, England for people with longer-term depression. Data and assumptions were synthesised to estimate cost per Quality Adjusted Life Years (QALYs). Results Three service changes were developed and resulted in increased QALYs at increased cost. Versus current care, the incremental cost-effectiveness ratio (ICER) for a self-referral service was £11,378 per QALY. The ICER was £2,227 per QALY for the dropout reduction service and £223 per QALY for an increase in non-therapy services. These results were robust when compared to current cost-effectiveness thresholds and accounting for uncertainty. Conclusions Cost-effective service improvements for longer-term depression have been identified. Also identified were limitations of the current evidence for the long term impact of services

Personal non-commercial use only

ABSTRACT. Objective. To compare the costs and benefits of alternative combination strategies of disease-modifying antirheumatic drugs (DMARD) and DMARD monotherapy in patients with early, active rheumatoid arthritis (RA). Methods. Data were drawn from randomized controlled trials that compared DMARD monotherapy or any DMARD combination strategy, with or without combined steroid therapy. Mixed treatment comparison methods were used to estimate the relative effectiveness of the different strategies. A mathematical model was developed to compare the longterm costs and benefits of the alternative strategies, combining data from a variety of sources. Costs were considered from a health sector viewpoint and benefits were expressed in terms of quality-adjusted life-years (QALY). Results. If decision makers use a threshold of £20,000 (US$29,000) per QALY, then the strategies most likely to be cost-effective are either DMARD combination therapy with downward titration (probability of being optimal = 0.50) or intensive, triple DMARD combination therapy (probability of being optimal = 0.43). The intensive DMARD strategy generated an additional cost of £27,392 per additional QALY gained compared to the downward titration strategy. Other combination strategies were unlikely to be considered cost-effective compared to DMARD monotherapy. Results were robust to a range of scenario sensitivity analyses. Conclusion. Combination DMARD therapy is likely to be cost-effective compared to DMARD monotherapy where treatment entails rapid downward dose titration or intensive, triple DMARD ther

Personal non-commercial use only. The Journal of RheumatologyJ Rheumatol First Release

ABSTRACT. Objective. To compare the costs and benefits of alternative combination strategies of disease-modifying antirheumatic drugs (DMARD) and DMARD monotherapy in patients with early, active rheumatoid arthritis (RA). Methods. Data were drawn from randomized controlled trials that compared DMARD monotherapy or any DMARD combination strategy, with or without combined steroid therapy. Mixed treatment comparison methods were used to estimate the relative effectiveness of the different strategies. A mathematical model was developed to compare the longterm costs and benefits of the alternative strategies, combining data from a variety of sources. Costs were considered from a health sector viewpoint and benefits were expressed in terms of quality-adjusted life-years (QALY). Results. If decision makers use a threshold of £20,000 (US$29,000) per QALY, then the strategies most likely to be cost-effective are either DMARD combination therapy with downward titration (probability of being optimal = 0.50) or intensive, triple DMARD combination therapy (probability of being optimal = 0.43). The intensive DMARD strategy generated an additional cost of £27,392 per additional QALY gained compared to the downward titration strategy. Other combination strategies were unlikely to be considered cost-effective compared to DMARD monotherapy. Results were robust to a range of scenario sensitivity analyses. Conclusion. Combination DMARD therapy is likely to be cost-effective compared to DMARD monotherapy where treatment entails rapid downward dose titration or intensive, triple DMARD therapy

Application of Constrained Optimization Methods in Health Services Research: Report 2 of the ISPOR Optimization Methods Emerging Good Practices Task Force

Background: Constrained optimization methods are already widely used in health care to solve problems that represent traditional applications of operations research methods, such as choosing the optimal location for new facilities or making the most efficient use of operating room capacity. Objectives: In this paper we illustrate the potential utility of these methods for finding optimal solutions to problems in health care delivery and policy. To do so, we selected three award-winning papers in health care delivery or policy development, reflecting a range of optimization algorithms. Two of the three papers are reviewed using the ISPOR Constrained Optimization Good Practice Checklist, adapted from the framework presented in the initial Optimization Task Force Report. The first case study illustrates application of linear programming to determine the optimal mix of screening and vaccination strategies for the prevention of cervical cancer. The second case illustrates application of the Markov Decision Process to find the optimal strategy for treating type 2 diabetes patients for hypercholesterolemia using statins. The third paper (described in Appendix 1) is used as an educational tool. The goal is to describe the characteristics of a radiation therapy optimization problem and then invite the reader to formulate the mathematical model for solving it. This example is particularly interesting because it lends itself to a range of possible models, including linear, nonlinear, and mixed-integer programming formulations. From the case studies presented, we hope the reader will develop an appreciation for the wide range of problem types that can be addressed with constrained optimization methods, as well as the variety of methods available. Conclusions: Constrained optimization methods are informative in providing insights to decision makers about optimal target solutions and the magnitude of the loss of benefit or increased costs associated with the ultimate clinical decision or policy choice. Failing to identify a mathematically superior or optimal solution represents a missed opportunity to improve economic efficiency in the delivery of care and clinical outcomes for patients. The ISPOR Optimization Methods Emerging Good Practices Task Force's first report provided an introduction to constrained optimization methods to solve important clinical and health policy problems. This report also outlined the relationship of constrained optimization methods relative to traditional health economic modeling, graphically illustrated a simple formulation, and identified some of the major variants of constrained optimization models, such as linear programming, dynamic programming, integer programming, and stochastic programming. The second report illustrates the application of constrained optimization methods in health care decision making using three case studies. The studies focus on determining optimal screening and vaccination strategies for cervical cancer, optimal statin start times for diabetes, and an educational case to invite the reader to formulate radiation therapy optimization problems. These illustrate a wide range of problem types that can be addressed with constrained optimization methods