PE Guidelines Key Features:
|Title and year of the document||Cleemput I, Neyt M, Van de Sande S, Thiry N. Belgian guidelines for economic evaluations and budget impact analyses: second edition. Health Technology Assessment (HTA). Brussels: Belgian Health Care Knowledge Centre(KCE). 2012. KCE Report 183C.|
|Affiliation of authors||Belgian Health Care Knowledge Centre (KCE).|
|Purpose of the document||These guidelines will support those who perform and assess economic evaluations and budget impact analyses. It may also support those involved in the development of study protocols.|
|Standard reporting format included||Yes (chapter 9)|
|Target audience of funding/ author's interests||Decision makers, researchers, pharmaceutical companies and producers of medical interventions.|
|Perspective||Costs: Health care payer (government + patients); Outcomes: society (for health-related quality of life: health state descriptions by patients, valuations from general public)|
|Target population||Consistent with the patient population defined in the clinical part of the reimbursement request submission.|
|Subgroup analysis||Yes. If the interventionís effectiveness and/or costs differ between subgroups, separate subgroup analyses should be performed. Post-hoc subgroup analyses are only allowed if the safety, effectiveness or costs between the subgroups are proven to be different based on appropriate statistical analyses or if the baseline risk for events differs between subgroups of the target population. Relative effectiveness should be assumed equal across subgroups in the latter case. The validity of this assumption should be checked.|
|Choice of comparator||For the identification of the appropriate comparator, the efficiency frontier should be constructed. This involves the identification of all relevant treatments for the targeted indication and population, the removal of dominated or extendedly dominated interventions from the list of relevant comparators, and the calculation of the incremental cost-effectiveness ratios (ICERs) of all interventions compared to the next best alternative. Off-label used pharmaceutical products can be used as valid comparators in a pharmacoeconomic evaluation if evidence is available about the clincial safety and efficacy of the off-label use, e.g. from government sponsored trials.|
|Time horizon||The appropriate time horizon for the economic evaluation depends on the duration of the impact of the study intervention on relevant costs and outcomes as compared to the comparator intervention.|
|Assumptions required||Yes. The number of assumptions not based on clinical evidence should be reduced to a minimum and be fully justified. Assumptions and sources of information should be justified and presented in a clear and transparent way.|
|Preferred analytical technique||Cost-effectiveness analysis should be used if improving life expectancy is the main objective of the treatment and also the most important outcome from the patientís point of view. Outcomes of cost-effectiveness analyses should be expressed in euro per life-year gained. Cost-utility analysis should be used if the treatment has an impact on health-related quality of life that is significant to the patient or if there are multiple patient-relevant clinical outcome parameters expressed in different units that cannot be translated into one common unit in a valid way. Outcomes of cost-utility analyses should be expressed in euro per quality-adjusted life year gained.|
|Costs to be included||The reference case should only include direct health care costs. These encompass costs directly related to the treatment of the disease as well as direct health care costs related to the disease in life years gained. Direct costs outside the health care sector, productivity costs and health care costs associated with unrelated diseases should not be included in the reference case, but may be reported as a separate analysis.|
|Source of costs||The identification, measurement and valuation of costs should be consistent with the perspective of the Belgian health care payers. Validated sources should be used for the unit costs.|
|Modeling||Yes. Modeling should be applied if the available data are insufficient to allow a full assessment of the cost-effectiveness or cost-utility of an intervention. Models should be based as much as possible on data from clinical studies with the same study intervention and comparator, on data from validated databases and/or data from literature.|
|Systematic review of evidences||Yes. Each economic evaluation should be accompanied by a description of the disease and the interventions studied and a systematic review of the existing relevant clinical literature. The review should reveal up-to-date evidence for clinical effectiveness of the intervention relative to its appropriate comparator(s). A review of economic studies is useful to identify relevant input parameters for the economic model and to support the assessors. The medical and economic search strategies should be reproducible and selection criteria and procedures clearly presented. The evidence should be critically appraised, its quality assessed and data presented in summary/evidence tables. A clear and concise synthesis, substantiated with references, should be provided. Ongoing studies should be mentioned.|
|Preference for effectiveness over efficacy||Yes. For reimbursement decisions, it is preferred that the outcome data used in economic evaluations reflect the interventionsí effectiveness in daily practice (i.e. effectiveness in contrast to efficacy). Because effectiveness data are usually not available (yet) at the time of the initial reimbursement request, efficacy results are often transposed to the real life target population to estimate effectiveness in a cost-effectiveness analysis. This is acceptable, as long as adjustments are made for baseline risk in the real life target population.|
|Preferred outcome measure||Outcomes in economic evaluations should be expressed in terms of final endpoints instead of intermediary outcomes. Clearly defined outcome measures, for which there is little debate about the measurement methods, are recommended.|
For cost-effectiveness analyses, outcomes should be expressed in terms of life years gained.
For cost-utility analyses, quality-adjusted life years (QALYs) should be calculated.
|Preferred method to derive utility||Health-related quality of life weights should be based on empirical data, obtained in patients with a descriptive system for health status for which corresponding preference values exist from the general public such as the EQ-5D.|
There is no golden standard for measuring utility. In order to stimulate the use of generic utility instruments and to promote consistency, the Belgian guidelines explicitly encourage the use of the EQ-5D instrument. If researchers feel that an intervention will have an impact on a patientís quality of life, including this instrument in the study protocol should be considered. This does not replace the use of disease-specific instruments, but rather complements them. If the EQ-5D instrument is not considered suitable, then the use of another generic utility instrument or direct measurement of utilities by means of time-trade-off (TTO) or standard gamble (SG) can be considered. This should then also be justified.
|Equity issues stated||As no weights that represent distributional preferences of the general public according to the populations affected are available, QALYs should not be weighted in the economic analysis. This means that in submitted economic evaluations a QALY is a QALY, no matter to whom it accrues.|
|Discounting costs||Future costs should be discounted at a rate of 3%|
|Discounting outcomes||Future benefits should be discounted atat a rate of 1.5%|
|Sensitivity analysis-parameters and range||Parameter uncertainty: This uncertainty is reflected in probability distributions based on a sample of data and is handled via probabilistic and one- or multiple-way sensitivity analyses.|
Interval estimates should be presented for each uncertain parameter in the economic evaluation. Structural and methodological uncertainty: uncertainty coming from the analytical methods chosen to perform the evaluation (e.g. health states in the model, discount rate or extrapolation methods). This type of uncertainty is usually handled by presenting results from a methodological reference case and other scenarios handled through one-way sensitivity analyses.
|Sensitivity analysis-methods||Probabilistic sensitivity analyses should be performed on all uncertain parameters in a model; i.e. one probabilistic sensitivity analysis where all uncertain parameters are allowed to vary according to a predefined distribution, e.g. by means of Monte Carlo simulations. Distributions used for the uncertain modeling parameters should be justified. |
The probabilistic sensitivity analysis should be performed on the reference case and the alternative scenarios.
|Presenting results||Results should be expressed as incremental costs, incremental effects and incremental cost-effectiveness or cost-utility ratios with their associated uncertainty. If a cost-utility ratio is presented as the result of a reference case analysis, the corresponding cost per life-year gained should also be presented.|
Uncertainty around the incremental costs, incremental effects and ICERs should be provided by means of confidence or credibility intervals. A cost-effectiveness plane and cost-effectiveness acceptability curve should be presented. The most important contributors to the uncertainty of the estimated incremental cost-effectiveness/cost-utility ratio should be shown.
|Total costs vs effectiveness (cost/effectiveness ratio)||Yes|
|Portability of results (Generalizability)||The patient population to which the pharmaco-economic evaluation applies should be consistent with the patient population defined in the clinical part of the reimbursement request submission.|
Generalizability refers to applicability of the results to other populations (e.g. non-trial populations with different baseline risk).
Post-hoc subgroup analyses are only allowed if the safety, effectiveness or costs between the subgroups are proven to be different based on appropriate statistical analyses or if the baseline risk for events differs between subgroups of the target population. Relative effectiveness should be assumed equal across subgroups in the latter case. The validity of this assumption should be checked.
|Financial impact analysis||Yes. See Chapter 6 "guidelines for budget impact analysis" (p 44-50).|
|Mandatory or recommended or voluntary||Mandatory|