The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smoking

<p>Abstract</p> <p>Background</p> <p>In response to the lack of comprehensive information about the health and economic benefits of quitting smoking for Australians, we developed the Quit Benefits Model (QBM).</p> <p>Methods</p> <p>The QBM is a M...

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Main Authors: Hurley Susan F, Matthews Jane P
Format: Article
Language:English
Published: BMC 2007-01-01
Series:Cost Effectiveness and Resource Allocation
Online Access:http://www.resource-allocation.com/content/5/1/2
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spelling doaj-7d17b18989934fe9ba293849c944356f2020-11-24T21:35:57ZengBMCCost Effectiveness and Resource Allocation1478-75472007-01-0151210.1186/1478-7547-5-2The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smokingHurley Susan FMatthews Jane P<p>Abstract</p> <p>Background</p> <p>In response to the lack of comprehensive information about the health and economic benefits of quitting smoking for Australians, we developed the Quit Benefits Model (QBM).</p> <p>Methods</p> <p>The QBM is a Markov model, programmed in TreeAge, that assesses the consequences of quitting in terms of cases avoided of the four most common smoking-associated diseases, deaths avoided, and quality-adjusted life-years (QALYs) and health care costs saved (in Australian dollars, A$). Quitting outcomes can be assessed for males and females in 14 five year age-groups from 15–19 to 80–84 years.</p> <p>Exponential models, based on data from large case-control and cohort studies, were developed to estimate the decline over time after quitting in the risk of acute myocardial infarction (AMI), stroke, lung cancer, chronic obstructive pulmonary disease (COPD), and death. Australian data for the year 2001 were sourced for disease incidence and mortality and health care costs. Utility of life estimates were sourced from an international registry and a meta analysis.</p> <p>In this paper, outcomes are reported for simulated subjects followed up for ten years after quitting smoking. Life-years, QALYs and costs were estimated with 0%, 3% and 5% per annum discount rates. Summary results are presented for a group of 1,000 simulated quitters chosen at random from the Australian population of smokers aged between 15 and 74.</p> <p>Results</p> <p>For every 1,000 males chosen at random from the reference population who quit smoking, there is a an average saving in the first ten years following quitting of A$408,000 in health care costs associated with AMI, COPD, lung cancer and stroke, and a corresponding saving of A$328,000 for every 1,000 female quitters. The average saving per 1,000 random quitters is A$373,000. Overall 40 of these quitters will be spared a diagnosis of AMI, COPD, lung cancer and stroke in the first ten years following quitting, with an estimated saving of 47 life-years and 75 QALYs. Sensitivity analyses indicated that QBM predictions were robust to variations of ± 10% in parameter estimates.</p> <p>Conclusion</p> <p>The QBM can answer many of the questions posed by Australian policy-makers and health program funders about the benefits of quitting, and is a useful tool to evaluate tobacco control programs. It can easily be re-programmed with updated information or a set of epidemiologic data from another country.</p> http://www.resource-allocation.com/content/5/1/2
collection DOAJ
language English
format Article
sources DOAJ
author Hurley Susan F
Matthews Jane P
spellingShingle Hurley Susan F
Matthews Jane P
The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smoking
Cost Effectiveness and Resource Allocation
author_facet Hurley Susan F
Matthews Jane P
author_sort Hurley Susan F
title The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smoking
title_short The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smoking
title_full The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smoking
title_fullStr The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smoking
title_full_unstemmed The Quit Benefits Model: a Markov model for assessing the health benefits and health care cost savings of quitting smoking
title_sort quit benefits model: a markov model for assessing the health benefits and health care cost savings of quitting smoking
publisher BMC
series Cost Effectiveness and Resource Allocation
issn 1478-7547
publishDate 2007-01-01
description <p>Abstract</p> <p>Background</p> <p>In response to the lack of comprehensive information about the health and economic benefits of quitting smoking for Australians, we developed the Quit Benefits Model (QBM).</p> <p>Methods</p> <p>The QBM is a Markov model, programmed in TreeAge, that assesses the consequences of quitting in terms of cases avoided of the four most common smoking-associated diseases, deaths avoided, and quality-adjusted life-years (QALYs) and health care costs saved (in Australian dollars, A$). Quitting outcomes can be assessed for males and females in 14 five year age-groups from 15–19 to 80–84 years.</p> <p>Exponential models, based on data from large case-control and cohort studies, were developed to estimate the decline over time after quitting in the risk of acute myocardial infarction (AMI), stroke, lung cancer, chronic obstructive pulmonary disease (COPD), and death. Australian data for the year 2001 were sourced for disease incidence and mortality and health care costs. Utility of life estimates were sourced from an international registry and a meta analysis.</p> <p>In this paper, outcomes are reported for simulated subjects followed up for ten years after quitting smoking. Life-years, QALYs and costs were estimated with 0%, 3% and 5% per annum discount rates. Summary results are presented for a group of 1,000 simulated quitters chosen at random from the Australian population of smokers aged between 15 and 74.</p> <p>Results</p> <p>For every 1,000 males chosen at random from the reference population who quit smoking, there is a an average saving in the first ten years following quitting of A$408,000 in health care costs associated with AMI, COPD, lung cancer and stroke, and a corresponding saving of A$328,000 for every 1,000 female quitters. The average saving per 1,000 random quitters is A$373,000. Overall 40 of these quitters will be spared a diagnosis of AMI, COPD, lung cancer and stroke in the first ten years following quitting, with an estimated saving of 47 life-years and 75 QALYs. Sensitivity analyses indicated that QBM predictions were robust to variations of ± 10% in parameter estimates.</p> <p>Conclusion</p> <p>The QBM can answer many of the questions posed by Australian policy-makers and health program funders about the benefits of quitting, and is a useful tool to evaluate tobacco control programs. It can easily be re-programmed with updated information or a set of epidemiologic data from another country.</p>
url http://www.resource-allocation.com/content/5/1/2
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