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Microsimulation Modeling of Coronary Heart Disease: Maximizing the Impact of Nonprofit Hospital–Based Interventions

We use microsimulation to forecast changes in coronary heart disease (CHD) among adults 45 or above over a 20-year time horizon in Los Angeles County (N = 3.4 million), a county with 12 635 CHD deaths in 2010. We simulate individuals’ life course and calibrate CHD trends to observed trends in the pa...

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Autores principales: Orenstein, Peggy Vadillo, Shi, Lu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798743/
https://www.ncbi.nlm.nih.gov/pubmed/27677519
http://dx.doi.org/10.1177/0046958016666009
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author Orenstein, Peggy Vadillo
Shi, Lu
author_facet Orenstein, Peggy Vadillo
Shi, Lu
author_sort Orenstein, Peggy Vadillo
collection PubMed
description We use microsimulation to forecast changes in coronary heart disease (CHD) among adults 45 or above over a 20-year time horizon in Los Angeles County (N = 3.4 million), a county with 12 635 CHD deaths in 2010. We simulate individuals’ life course and calibrate CHD trends to observed trends in the past. Using the Health Forecasting Community Health Simulation Model, we simulate CHD prevalence and CHD mortality in 2 CHD prevention scenarios: (1) “comprehensive hypertension intervention” and (2) “gradual reduction of the average adult body mass index back to the year 2000 level.” We use microsimulation methodology so that nonprofit hospitals can easily use our model to forecast intervention results in their specific hospital catchment area. Our baseline model (without intervention) forecasts an increase in CHD prevalence that will reach 13.01% among those 45+ in Los Angeles County in 2030. Under scenario 1, the increase in CHD prevalence is slower (12.47% in 2030), and the prevalence in scenario 2 reaches 12.83% in 2030. The baseline scenario projects a number of 21 300 CHD deaths in 2030, whereas there will be 20 070 CHD deaths under scenario 1 and 20 970 CHD deaths under scenario 2. At the population level, the CHD mortality outcome, as compared with the metric of CHD prevalence, might be more sensitive to preventive lifestyle interventions. Both CHD prevalence and CHD mortality might be more sensitive to the hypertension intervention than to the obesity reduction in the time horizon of 20 years.
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spelling pubmed-57987432018-02-12 Microsimulation Modeling of Coronary Heart Disease: Maximizing the Impact of Nonprofit Hospital–Based Interventions Orenstein, Peggy Vadillo Shi, Lu Inquiry Original Research We use microsimulation to forecast changes in coronary heart disease (CHD) among adults 45 or above over a 20-year time horizon in Los Angeles County (N = 3.4 million), a county with 12 635 CHD deaths in 2010. We simulate individuals’ life course and calibrate CHD trends to observed trends in the past. Using the Health Forecasting Community Health Simulation Model, we simulate CHD prevalence and CHD mortality in 2 CHD prevention scenarios: (1) “comprehensive hypertension intervention” and (2) “gradual reduction of the average adult body mass index back to the year 2000 level.” We use microsimulation methodology so that nonprofit hospitals can easily use our model to forecast intervention results in their specific hospital catchment area. Our baseline model (without intervention) forecasts an increase in CHD prevalence that will reach 13.01% among those 45+ in Los Angeles County in 2030. Under scenario 1, the increase in CHD prevalence is slower (12.47% in 2030), and the prevalence in scenario 2 reaches 12.83% in 2030. The baseline scenario projects a number of 21 300 CHD deaths in 2030, whereas there will be 20 070 CHD deaths under scenario 1 and 20 970 CHD deaths under scenario 2. At the population level, the CHD mortality outcome, as compared with the metric of CHD prevalence, might be more sensitive to preventive lifestyle interventions. Both CHD prevalence and CHD mortality might be more sensitive to the hypertension intervention than to the obesity reduction in the time horizon of 20 years. SAGE Publications 2016-09-26 /pmc/articles/PMC5798743/ /pubmed/27677519 http://dx.doi.org/10.1177/0046958016666009 Text en © The Author(s) 2016 http://creativecommons.org/licenses/by-nc/3.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://www.creativecommons.org/licenses/by-nc/3.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page(https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Orenstein, Peggy Vadillo
Shi, Lu
Microsimulation Modeling of Coronary Heart Disease: Maximizing the Impact of Nonprofit Hospital–Based Interventions
title Microsimulation Modeling of Coronary Heart Disease: Maximizing the Impact of Nonprofit Hospital–Based Interventions
title_full Microsimulation Modeling of Coronary Heart Disease: Maximizing the Impact of Nonprofit Hospital–Based Interventions
title_fullStr Microsimulation Modeling of Coronary Heart Disease: Maximizing the Impact of Nonprofit Hospital–Based Interventions
title_full_unstemmed Microsimulation Modeling of Coronary Heart Disease: Maximizing the Impact of Nonprofit Hospital–Based Interventions
title_short Microsimulation Modeling of Coronary Heart Disease: Maximizing the Impact of Nonprofit Hospital–Based Interventions
title_sort microsimulation modeling of coronary heart disease: maximizing the impact of nonprofit hospital–based interventions
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5798743/
https://www.ncbi.nlm.nih.gov/pubmed/27677519
http://dx.doi.org/10.1177/0046958016666009
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