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

Gian Luca Di Tanna, Anna Bychenkova, Frank O’Neill, Heidi S. Wirtz, Paul Miller, Briain Ó Hartaigh and Gary Globe ()
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Gian Luca Di Tanna: Economic Modelling Centre of Excellence, Amgen (Europe) GmbH
Anna Bychenkova: Global Health Economics, Amgen Inc
Frank O’Neill: Global Health Economics, Amgen Inc
Heidi S. Wirtz: Amgen Inc., One Amgen Center Drive
Paul Miller: Miller Economics Ltd
Briain Ó Hartaigh: Envision Pharma Group
Gary Globe: Amgen Inc., One Amgen Center Drive

PharmacoEconomics, 2019, vol. 37, issue 3, No 5, 359-389

Abstract: Abstract 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.

Date: 2019
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DOI: 10.1007/s40273-018-0755-x

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