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Modeling the Impact of Increased Adherence to Asthma Therapy
BACKGROUND: Nonadherence to medications occurs in up to 70% of patients with asthma. The effect of improving adherence is not well quantified. We developed a mathematical model with which to assess the population-level effects of improving medication prescribing and adherence for asthma. METHODS: A...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3517627/ https://www.ncbi.nlm.nih.gov/pubmed/23236442 http://dx.doi.org/10.1371/journal.pone.0051139 |
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author | Schlender, Amory Alperin, Peter E. Grossman, Helene L. Sutherland, E. Rand |
author_facet | Schlender, Amory Alperin, Peter E. Grossman, Helene L. Sutherland, E. Rand |
author_sort | Schlender, Amory |
collection | PubMed |
description | BACKGROUND: Nonadherence to medications occurs in up to 70% of patients with asthma. The effect of improving adherence is not well quantified. We developed a mathematical model with which to assess the population-level effects of improving medication prescribing and adherence for asthma. METHODS: A mathematical model, calibrated to clinical trial data from the U.S. NHLBI-funded SOCS trial and validated using data from the NHLBI SLIC trial, was used to model the effects of increased prescribing and adherence to asthma controllers. The simulated population consisted of 4,930 individuals with asthma, derived from a sample the National Asthma Survey. Main outcomes were controller use, reliever use, unscheduled doctor visits, emergency department (ED) visits, and hospitalizations. RESULTS: For the calibration, simulated outcomes agreed closely with SOCS trial outcomes, with treatment failure hazard ratios [95% confidence interval] of 0.92 [0.58–1.26], 0.97 [0.49–1.45], and 1.01 [0–1.87] for simulation vs. trial in the in placebo, salmeterol, and triamcinolone arms, respectively. For validation, simulated outcomes predicted mid- and end-point treatment failure rates, hazard ratios 1.21 [0.08–2.34] and 0.83 [0.60–1.07], respectively, for patients treated with salmeterol/triamcinolone during the first half of the SLIC study and salmeterol monotherapy during the second half. The model performed less well for patients treated with salmeterol/triamcinolone during the entire study duration, with mid- and end-point hazard ratios 0.83 [0.00–2.12] and 0.37 [0.10–0.65], respectively. Simulation of optimal adherence and prescribing indicated that closing adherence and prescription gaps could prevent as many as nine million unscheduled doctor visits, four million emergency department visits, and one million asthma-related hospitalizations each year in the U.S. CONCLUSIONS: Improvements in medication adherence and prescribing could have a substantial impact on asthma morbidity and healthcare utilization. |
format | Online Article Text |
id | pubmed-3517627 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-35176272012-12-12 Modeling the Impact of Increased Adherence to Asthma Therapy Schlender, Amory Alperin, Peter E. Grossman, Helene L. Sutherland, E. Rand PLoS One Research Article BACKGROUND: Nonadherence to medications occurs in up to 70% of patients with asthma. The effect of improving adherence is not well quantified. We developed a mathematical model with which to assess the population-level effects of improving medication prescribing and adherence for asthma. METHODS: A mathematical model, calibrated to clinical trial data from the U.S. NHLBI-funded SOCS trial and validated using data from the NHLBI SLIC trial, was used to model the effects of increased prescribing and adherence to asthma controllers. The simulated population consisted of 4,930 individuals with asthma, derived from a sample the National Asthma Survey. Main outcomes were controller use, reliever use, unscheduled doctor visits, emergency department (ED) visits, and hospitalizations. RESULTS: For the calibration, simulated outcomes agreed closely with SOCS trial outcomes, with treatment failure hazard ratios [95% confidence interval] of 0.92 [0.58–1.26], 0.97 [0.49–1.45], and 1.01 [0–1.87] for simulation vs. trial in the in placebo, salmeterol, and triamcinolone arms, respectively. For validation, simulated outcomes predicted mid- and end-point treatment failure rates, hazard ratios 1.21 [0.08–2.34] and 0.83 [0.60–1.07], respectively, for patients treated with salmeterol/triamcinolone during the first half of the SLIC study and salmeterol monotherapy during the second half. The model performed less well for patients treated with salmeterol/triamcinolone during the entire study duration, with mid- and end-point hazard ratios 0.83 [0.00–2.12] and 0.37 [0.10–0.65], respectively. Simulation of optimal adherence and prescribing indicated that closing adherence and prescription gaps could prevent as many as nine million unscheduled doctor visits, four million emergency department visits, and one million asthma-related hospitalizations each year in the U.S. CONCLUSIONS: Improvements in medication adherence and prescribing could have a substantial impact on asthma morbidity and healthcare utilization. Public Library of Science 2012-12-07 /pmc/articles/PMC3517627/ /pubmed/23236442 http://dx.doi.org/10.1371/journal.pone.0051139 Text en © 2012 Schlender et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Schlender, Amory Alperin, Peter E. Grossman, Helene L. Sutherland, E. Rand Modeling the Impact of Increased Adherence to Asthma Therapy |
title | Modeling the Impact of Increased Adherence to Asthma Therapy |
title_full | Modeling the Impact of Increased Adherence to Asthma Therapy |
title_fullStr | Modeling the Impact of Increased Adherence to Asthma Therapy |
title_full_unstemmed | Modeling the Impact of Increased Adherence to Asthma Therapy |
title_short | Modeling the Impact of Increased Adherence to Asthma Therapy |
title_sort | modeling the impact of increased adherence to asthma therapy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3517627/ https://www.ncbi.nlm.nih.gov/pubmed/23236442 http://dx.doi.org/10.1371/journal.pone.0051139 |
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