Comparative Effectiveness Health Insurance International Health Care Systems Public Health Public Policy Regulation

What does a NICE health economist do?

What role do health economists at the UK’s National Institute for Health and Clinical Excellence (NICE) play and how do they conduct their cost effectiveness analyses for new treatments? I answer this question today based on NICE’s own documents.  According to their guidelines manual, the role of the health economist in clinical guideline development is to:

  • advise on economic issues
  • review economic evaluations
  • prioritize questions for further economic analysis
  • conduct economic evaluations
  • liaise with the costing analyst at NICE to ensure consistency between the cost-effectiveness and cost-impact assessments

National Collaborating Centre (NCC) prepares an economic plan, which contains a preliminary overview of the relevant economic literature. The plan also identifies the initial priorities for further economic analysis and the proposed methods for addressing these questions.

The NICE document notes that “economic analysis is not simply a matter of estimating the consequences of a guideline recommendation in terms of use of resources, but is concerned with the evaluation of both costs and health benefits.” The health economist, in concert with the guideline development group (GDG) is directed by NICE to consider recommendations for interventions that:

  • are less effective than current practice but free up a substantial amount of resources that can be re-invested in the NHS, or
  • increase clinical effectiveness at an acceptable level of increased cost

Typically, a health economist will review the literature and find that additional analyses will be helpful for determining NICE guidelines. Additional analyses, however, can be expensive. NICE prioritizes the following analyses based on:

  • the overall ‘importance’ of the recommendation (which is a function of the number of patients affected and the potential impact on costs and health outcomes per patient)
  • the current extent of uncertainty over cost effectiveness, and the likelihood that economic analysis will reduce this uncertainty.

Most NICE cost-effectiveness studies use rely on determining the treatment’s cost per increase in quality-adjusted life years (QALYs). To estimate this quantity, NICE health economists often model their projections around a single well-conducted randomized controlled trial, or by using decision-analytic techniques with probability, cost and health outcome data from a variety of published sources.

What is the proper scope of the analysis. NICE guidelines are as follows:

For the reference case, the perspective on outcomes should be all direct health effects, whether for patients or, when relevant, other people (principally carers). The perspective on costs should be that of the NHS and PSS. Some interventions may have a substantial impact on non-health outcomes or costs to other government bodies (for example, treatments to reduce illicit drug misuse may have the effect of reducing drug-related crime). If costs to other government bodies are believed to be significant, they may be included in a sensitivity analysis and presented alongside the reference case results. Productivity costs and costs borne by patients and carers that are not reimbursed by the NHS or PSS should not be included in any analyses.

‘Sensitivity analysis should be used to explore the impact of potential sources of bias and uncertainty on model results. Potential bias resulting from key structural assumptions should be explored through deterministic sensitivity analyses, testing whether and how the model results change under alternative plausible scenarios. Deterministic sensitivity analysis should also be used to test the impact of potential bias resulting from the selection of data sources for key model parameters. Probabilistic sensitivity analysis is preferred for exploring uncertainty arising from imprecision in model parameters. This enables the uncertainty associated with all parameters to be reflected simultaneously in the results. In nonlinear decision models, probabilistic methods also provide the best estimates of mean costs and outcomes. However, models incorporating probabilistic methods are more time-consuming to construct and may not always be a priority for health economists working on clinical guidelines. In such cases, the decision not to use probabilistic methods should be clearly stated and justified in the full guideline, and the impact of parameter uncertainty should be thoroughly explored through deterministic sensitivity analysis.


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