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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-prac...

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Autores principales: Di Tanna, Gian Luca, Bychenkova, Anna, O’Neill, Frank, Wirtz, Heidi S., Miller, Paul, Ó Hartaigh, Briain, Globe, Gary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386015/
https://www.ncbi.nlm.nih.gov/pubmed/30596210
http://dx.doi.org/10.1007/s40273-018-0755-x
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author Di Tanna, Gian Luca
Bychenkova, Anna
O’Neill, Frank
Wirtz, Heidi S.
Miller, Paul
Ó Hartaigh, Briain
Globe, Gary
author_facet Di Tanna, Gian Luca
Bychenkova, Anna
O’Neill, Frank
Wirtz, Heidi S.
Miller, Paul
Ó Hartaigh, Briain
Globe, Gary
author_sort Di Tanna, Gian Luca
collection PubMed
description 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40273-018-0755-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-63860152019-03-12 Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review Di Tanna, Gian Luca Bychenkova, Anna O’Neill, Frank Wirtz, Heidi S. Miller, Paul Ó Hartaigh, Briain Globe, Gary Pharmacoeconomics Systematic 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40273-018-0755-x) contains supplementary material, which is available to authorized users. Springer International Publishing 2018-12-31 2019 /pmc/articles/PMC6386015/ /pubmed/30596210 http://dx.doi.org/10.1007/s40273-018-0755-x Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Systematic Review
Di Tanna, Gian Luca
Bychenkova, Anna
O’Neill, Frank
Wirtz, Heidi S.
Miller, Paul
Ó Hartaigh, Briain
Globe, Gary
Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review
title Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review
title_full Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review
title_fullStr Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review
title_full_unstemmed Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review
title_short Evaluating Cost-Effectiveness Models for Pharmacologic Interventions in Adults with Heart Failure: A Systematic Literature Review
title_sort evaluating cost-effectiveness models for pharmacologic interventions in adults with heart failure: a systematic literature review
topic Systematic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6386015/
https://www.ncbi.nlm.nih.gov/pubmed/30596210
http://dx.doi.org/10.1007/s40273-018-0755-x
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