Cargando…
Defining and Measuring Chronic Conditions: Imperatives for Research, Policy, Program, and Practice
Current trends in US population growth, age distribution, and disease dynamics foretell rises in the prevalence of chronic diseases and other chronic conditions. These trends include the rapidly growing population of older adults, the increasing life expectancy associated with advances in public hea...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Centers for Disease Control and Prevention
2013
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652713/ https://www.ncbi.nlm.nih.gov/pubmed/23618546 http://dx.doi.org/10.5888/pcd10.120239 |
_version_ | 1782269335591452672 |
---|---|
author | Goodman, Richard A. Posner, Samuel F. Huang, Elbert S. Parekh, Anand K. Koh, Howard K. |
author_facet | Goodman, Richard A. Posner, Samuel F. Huang, Elbert S. Parekh, Anand K. Koh, Howard K. |
author_sort | Goodman, Richard A. |
collection | PubMed |
description | Current trends in US population growth, age distribution, and disease dynamics foretell rises in the prevalence of chronic diseases and other chronic conditions. These trends include the rapidly growing population of older adults, the increasing life expectancy associated with advances in public health and clinical medicine, the persistently high prevalence of some risk factors, and the emerging high prevalence of multiple chronic conditions. Although preventing and mitigating the effect of chronic conditions requires sufficient measurement capacities, such measurement has been constrained by lack of consistency in definitions and diagnostic classification schemes and by heterogeneity in data systems and methods of data collection. We outline a conceptual model for improving understanding of and standardizing approaches to defining, identifying, and using information about chronic conditions in the United States. We illustrate this model’s operation by applying a standard classification scheme for chronic conditions to 5 national-level data systems. |
format | Online Article Text |
id | pubmed-3652713 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Centers for Disease Control and Prevention |
record_format | MEDLINE/PubMed |
spelling | pubmed-36527132013-05-20 Defining and Measuring Chronic Conditions: Imperatives for Research, Policy, Program, and Practice Goodman, Richard A. Posner, Samuel F. Huang, Elbert S. Parekh, Anand K. Koh, Howard K. Prev Chronic Dis Special Topic Current trends in US population growth, age distribution, and disease dynamics foretell rises in the prevalence of chronic diseases and other chronic conditions. These trends include the rapidly growing population of older adults, the increasing life expectancy associated with advances in public health and clinical medicine, the persistently high prevalence of some risk factors, and the emerging high prevalence of multiple chronic conditions. Although preventing and mitigating the effect of chronic conditions requires sufficient measurement capacities, such measurement has been constrained by lack of consistency in definitions and diagnostic classification schemes and by heterogeneity in data systems and methods of data collection. We outline a conceptual model for improving understanding of and standardizing approaches to defining, identifying, and using information about chronic conditions in the United States. We illustrate this model’s operation by applying a standard classification scheme for chronic conditions to 5 national-level data systems. Centers for Disease Control and Prevention 2013-04-25 /pmc/articles/PMC3652713/ /pubmed/23618546 http://dx.doi.org/10.5888/pcd10.120239 Text en https://creativecommons.org/licenses/by/4.0/This is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited. |
spellingShingle | Special Topic Goodman, Richard A. Posner, Samuel F. Huang, Elbert S. Parekh, Anand K. Koh, Howard K. Defining and Measuring Chronic Conditions: Imperatives for Research, Policy, Program, and Practice |
title | Defining and Measuring Chronic Conditions: Imperatives for Research, Policy, Program, and Practice |
title_full | Defining and Measuring Chronic Conditions: Imperatives for Research, Policy, Program, and Practice |
title_fullStr | Defining and Measuring Chronic Conditions: Imperatives for Research, Policy, Program, and Practice |
title_full_unstemmed | Defining and Measuring Chronic Conditions: Imperatives for Research, Policy, Program, and Practice |
title_short | Defining and Measuring Chronic Conditions: Imperatives for Research, Policy, Program, and Practice |
title_sort | defining and measuring chronic conditions: imperatives for research, policy, program, and practice |
topic | Special Topic |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3652713/ https://www.ncbi.nlm.nih.gov/pubmed/23618546 http://dx.doi.org/10.5888/pcd10.120239 |
work_keys_str_mv | AT goodmanricharda definingandmeasuringchronicconditionsimperativesforresearchpolicyprogramandpractice AT posnersamuelf definingandmeasuringchronicconditionsimperativesforresearchpolicyprogramandpractice AT huangelberts definingandmeasuringchronicconditionsimperativesforresearchpolicyprogramandpractice AT parekhanandk definingandmeasuringchronicconditionsimperativesforresearchpolicyprogramandpractice AT kohhowardk definingandmeasuringchronicconditionsimperativesforresearchpolicyprogramandpractice |