Estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from Germany: Markov modelling

<p>Abstract</p> <p>Background</p> <p>Type 2 diabetes mellitus (T2D) poses a large worldwide burden for health care systems. One possible tool to decrease this burden is primary prevention. As it is unethical to wait until perfect data are available to conclude whether T...

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Main Authors: Neumann Anne, Schwarz Peter, Lindholm Lars
Format: Article
Language:English
Published: BMC 2011-11-01
Series:Cost Effectiveness and Resource Allocation
Subjects:
Online Access:http://www.resource-allocation.com/content/9/1/17
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spelling doaj-8763b156ea164af08ba5fe254cf2c2b82020-11-25T01:00:41ZengBMCCost Effectiveness and Resource Allocation1478-75472011-11-01911710.1186/1478-7547-9-17Estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from Germany: Markov modellingNeumann AnneSchwarz PeterLindholm Lars<p>Abstract</p> <p>Background</p> <p>Type 2 diabetes mellitus (T2D) poses a large worldwide burden for health care systems. One possible tool to decrease this burden is primary prevention. As it is unethical to wait until perfect data are available to conclude whether T2D primary prevention intervention programmes are cost-effective, we need a model that simulates the effect of prevention initiatives. Thus, the aim of this study is to investigate the long-term cost-effectiveness of lifestyle intervention programmes for the prevention of T2D using a Markov model. As decision makers often face difficulties in applying health economic results, we visualise our results with health economic tools.</p> <p>Methods</p> <p>We use four-state Markov modelling with a probabilistic cohort analysis to calculate the cost per quality-adjusted life year (QALY) gained. A one-year cycle length and a lifetime time horizon are applied. Best available evidence supplies the model with data on transition probabilities between glycaemic states, mortality risks, utility weights, and disease costs. The costs are calculated from a societal perspective. A 3% discount rate is used for costs and QALYs. Cost-effectiveness acceptability curves are presented to assist decision makers.</p> <p>Results</p> <p>The model indicates that diabetes prevention interventions have the potential to be cost-effective, but the outcome reveals a high level of uncertainty. Incremental cost-effectiveness ratios (ICERs) were negative for the intervention, ie, the intervention leads to a cost reduction for men and women aged 30 or 50 years at initiation of the intervention. For men and women aged 70 at initiation of the intervention, the ICER was EUR27,546/QALY gained and EUR19,433/QALY gained, respectively. In all cases, the QALYs gained were low. Cost-effectiveness acceptability curves show that the higher the willingness-to-pay threshold value, the higher the probability that the intervention is cost-effective. Nonetheless, all curves are flat. The threshold value of EUR50,000/QALY gained has a 30-55% probability that the intervention is cost-effective.</p> <p>Conclusions</p> <p>Lifestyle interventions for primary prevention of type 2 diabetes are cost-saving for men and women aged 30 or 50 years at the start of the intervention, and cost-effective for men and women aged 70 years. However, there is a high degree of uncertainty around the ICERs. With the conservative approach adopted for this model, the long-term effectiveness of the intervention could be underestimated.</p> http://www.resource-allocation.com/content/9/1/17Diabetes mellitushealth care costshealth care economics and organisationsprimary preventionlife styleearly interventiondecision making
collection DOAJ
language English
format Article
sources DOAJ
author Neumann Anne
Schwarz Peter
Lindholm Lars
spellingShingle Neumann Anne
Schwarz Peter
Lindholm Lars
Estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from Germany: Markov modelling
Cost Effectiveness and Resource Allocation
Diabetes mellitus
health care costs
health care economics and organisations
primary prevention
life style
early intervention
decision making
author_facet Neumann Anne
Schwarz Peter
Lindholm Lars
author_sort Neumann Anne
title Estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from Germany: Markov modelling
title_short Estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from Germany: Markov modelling
title_full Estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from Germany: Markov modelling
title_fullStr Estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from Germany: Markov modelling
title_full_unstemmed Estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from Germany: Markov modelling
title_sort estimating the cost-effectiveness of lifestyle intervention programmes to prevent diabetes based on an example from germany: markov modelling
publisher BMC
series Cost Effectiveness and Resource Allocation
issn 1478-7547
publishDate 2011-11-01
description <p>Abstract</p> <p>Background</p> <p>Type 2 diabetes mellitus (T2D) poses a large worldwide burden for health care systems. One possible tool to decrease this burden is primary prevention. As it is unethical to wait until perfect data are available to conclude whether T2D primary prevention intervention programmes are cost-effective, we need a model that simulates the effect of prevention initiatives. Thus, the aim of this study is to investigate the long-term cost-effectiveness of lifestyle intervention programmes for the prevention of T2D using a Markov model. As decision makers often face difficulties in applying health economic results, we visualise our results with health economic tools.</p> <p>Methods</p> <p>We use four-state Markov modelling with a probabilistic cohort analysis to calculate the cost per quality-adjusted life year (QALY) gained. A one-year cycle length and a lifetime time horizon are applied. Best available evidence supplies the model with data on transition probabilities between glycaemic states, mortality risks, utility weights, and disease costs. The costs are calculated from a societal perspective. A 3% discount rate is used for costs and QALYs. Cost-effectiveness acceptability curves are presented to assist decision makers.</p> <p>Results</p> <p>The model indicates that diabetes prevention interventions have the potential to be cost-effective, but the outcome reveals a high level of uncertainty. Incremental cost-effectiveness ratios (ICERs) were negative for the intervention, ie, the intervention leads to a cost reduction for men and women aged 30 or 50 years at initiation of the intervention. For men and women aged 70 at initiation of the intervention, the ICER was EUR27,546/QALY gained and EUR19,433/QALY gained, respectively. In all cases, the QALYs gained were low. Cost-effectiveness acceptability curves show that the higher the willingness-to-pay threshold value, the higher the probability that the intervention is cost-effective. Nonetheless, all curves are flat. The threshold value of EUR50,000/QALY gained has a 30-55% probability that the intervention is cost-effective.</p> <p>Conclusions</p> <p>Lifestyle interventions for primary prevention of type 2 diabetes are cost-saving for men and women aged 30 or 50 years at the start of the intervention, and cost-effective for men and women aged 70 years. However, there is a high degree of uncertainty around the ICERs. With the conservative approach adopted for this model, the long-term effectiveness of the intervention could be underestimated.</p>
topic Diabetes mellitus
health care costs
health care economics and organisations
primary prevention
life style
early intervention
decision making
url http://www.resource-allocation.com/content/9/1/17
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AT lindholmlars estimatingthecosteffectivenessoflifestyleinterventionprogrammestopreventdiabetesbasedonanexamplefromgermanymarkovmodelling
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