Estimating the cost effectiveness of ramipril used for specific clinical indications: comparing the outcomes in four clinical trials with a common economic model

Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review

BACKGROUND

Heart failure (HF) is a well-recognized public health concern and imposes high economic and societal costs. Decision analytic models exist for evaluating the economic ramifications associated with HF. Despite this, studies that appraise these modelling approaches for augmenting best-practice decisions remain scarce.

OBJECTIVE

Our objective was to conduct a systematic literature review (SLR) of published economic models for the management of HF and describe their general and methodological features.

METHODS

This SLR employed a combination of relevant search terms associated with HF, which were used in a number of databases, including MEDLINE, Embase, the National Health Service Economic Evaluation Database, Cost-Effectiveness Analysis Registry, ScHARR Health Utilities Database and Cochrane Library Database. A number of model features (i.e. model structure, specification, outcomes assessed, scenario and sensitivity analysis, key model drivers) were extracted and subsequently summarized.

RESULTS

Of 64 publications retained, a selection of modelling approaches were identified, including Markov (n = 28), trial-based analytic (n = 22), discrete-event simulation (n = 6), survival analytic (n = 7) and decision-tree modelling (n = 1) approaches. The bulk of publications employed either a cost-utility (n = 27) or cost-effectiveness (n = 36) analysis and evaluated more than one study outcome, which typically included overall costs (n = 59), incremental cost-effectiveness ratios (n = 55), life-years gained (n = 48) and willingness-to-pay thresholds (n = 37). Most publications focused on patients with chronic HF (n = 40) and used New York Heart Association (NYHA) disease classifications to categorize patients and determine disease severity. Few (n = 19) publications documented the use of hospitalization states for modelling patient outcomes and associated costs. A quality assessment of the included publications revealed most articles demonstrated reasonable methodological value.

CONCLUSIONS

We identified numerous decision analytic modelling approaches for evaluating the cost effectiveness of pharmacologic treatments in HF. A Markov cohort model approach was most commonly used, and most models relied on NYHA classes as a proxy of HF severity, disease progression and prognosis.

Estimating the payoffs from cardiovascular disease research in Canada: an economic analysis

BACKGROUND

Investments in medical research can result in health improvements, reductions in health expenditures and secondary economic benefits. These "returns" have not been quantified in Canada. Our objective was to estimate the return on cardiovascular disease research funded by public or charitable organizations.

METHODS

Our primary outcome was the internal rate of return on cardiovascular disease research funded by public or charitable sources. The internal rate of return is the annual monetary benefit to the economy for each dollar invested in cardiovascular disease research. Calculation of the internal rate of return involved the following: measuring expenditures on cardiovascular disease research, estimating the health gains accrued from new treatments for cardiovascular disease, determining the proportion of health gains attributable to cardiovascular disease research and the time lag between research expenditures and health gains, and estimating the spillovers from public- or charitable-sector investments to other sectors of the economy.

RESULTS

Expenditures by public or charitable organizations on cardiovascular disease research from 1981 to 1992 amounted to $392 million (2005 dollars). Health gains associated with new treatments from 1994 to 2005 (13-yr lag) amounted to 2.2 million quality-adjusted life-years. We calculated an internal rate of return of 20.6%.

CONCLUSION

Canadians obtain relatively high health and economic gains from investments in cardiovascular disease research. Every $1 invested in cardiovascular disease research by public or charitable sources yields a stream of benefits of roughly $0.21 to the Canadian economy per year, in perpetuity.

Model performance evaluation (validation and calibration) in model-based studies of therapeutic interventions for cardiovascular diseases : a review and suggested reporting framework

Decision analytic models play an increasingly important role in the economic evaluation of health technologies. Given uncertainties around the assumptions used to develop such models, several guidelines have been published to identify and assess 'best practice' in the model development process, including general modelling approach (e.g., time horizon), model structure, input data and model performance evaluation. This paper focuses on model performance evaluation. In the absence of a sufficient level of detail around model performance evaluation, concerns regarding the accuracy of model outputs, and hence the credibility of such models, are frequently raised. Following presentation of its components, a review of the application and reporting of model performance evaluation is presented. Taking cardiovascular disease as an illustrative example, the review investigates the use of face validity, internal validity, external validity, and cross model validity. As a part of the performance evaluation process, model calibration is also discussed and its use in applied studies investigated. The review found that the application and reporting of model performance evaluation across 81 studies of treatment for cardiovascular disease was variable. Cross-model validation was reported in 55 % of the reviewed studies, though the level of detail provided varied considerably. We found that very few studies documented other types of validity, and only 6 % of the reviewed articles reported a calibration process. Considering the above findings, we propose a comprehensive model performance evaluation framework (checklist), informed by a review of best-practice guidelines. This framework provides a basis for more accurate and consistent documentation of model performance evaluation. This will improve the peer review process and the comparability of modelling studies. Recognising the fundamental role of decision analytic models in informing public funding decisions, the proposed framework should usefully inform guidelines for preparing submissions to reimbursement bodies.