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Influence of Using Different Databases and ‘Look Back’ Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers

OBJECTIVE: To determine the data sources and ‘look back’ intervals to define comorbidities. DATA SOURCES: Hospital discharge abstracts database (DAD), physician claims, population registry and death registry from April 1, 1994 to March 31, 2010 in Alberta, Canada. STUDY DESIGN: Newly-diagnosed hyper...

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Autores principales: Chen, Guanmin, Lix, Lisa, Tu, Karen, Hemmelgarn, Brenda R., Campbell, Norm R. C., McAlister, Finlay A., Quan, Hude
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5008755/
https://www.ncbi.nlm.nih.gov/pubmed/27583532
http://dx.doi.org/10.1371/journal.pone.0162074
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author Chen, Guanmin
Lix, Lisa
Tu, Karen
Hemmelgarn, Brenda R.
Campbell, Norm R. C.
McAlister, Finlay A.
Quan, Hude
author_facet Chen, Guanmin
Lix, Lisa
Tu, Karen
Hemmelgarn, Brenda R.
Campbell, Norm R. C.
McAlister, Finlay A.
Quan, Hude
author_sort Chen, Guanmin
collection PubMed
description OBJECTIVE: To determine the data sources and ‘look back’ intervals to define comorbidities. DATA SOURCES: Hospital discharge abstracts database (DAD), physician claims, population registry and death registry from April 1, 1994 to March 31, 2010 in Alberta, Canada. STUDY DESIGN: Newly-diagnosed hypertension cases from 1997 to 2008 fiscal years were identified and followed up to 12 years. We defined comorbidities using data sources and duration of retrospective observation (6 months, 1 year, 2 years, and 3 years). The C-statistics for logistic regression and concordance index (CI) for Cox model of mortality and cardiovascular disease hospitalization were used to evaluate discrimination performance for each approach of defining comorbidities. PRINCIPAL FINDINGS: The comorbidities prevalence became higher with a longer duration. Using DAD alone underestimated the prevalence by about 75%, compared to using both DAD and physician claims. The C-statistic and CI were highest when both DAD and physician claims were used, and model performance improved when observation duration increased from 6 months to one year or longer. CONCLUSION: The comorbidities prevalence is greatly impacted by the data source and duration of retrospective observation. A combination of DAD and physicians claims with at least one year observation duration improves predictions for cardiovascular disease and one-year mortality outcome model performance.
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spelling pubmed-50087552016-09-27 Influence of Using Different Databases and ‘Look Back’ Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers Chen, Guanmin Lix, Lisa Tu, Karen Hemmelgarn, Brenda R. Campbell, Norm R. C. McAlister, Finlay A. Quan, Hude PLoS One Research Article OBJECTIVE: To determine the data sources and ‘look back’ intervals to define comorbidities. DATA SOURCES: Hospital discharge abstracts database (DAD), physician claims, population registry and death registry from April 1, 1994 to March 31, 2010 in Alberta, Canada. STUDY DESIGN: Newly-diagnosed hypertension cases from 1997 to 2008 fiscal years were identified and followed up to 12 years. We defined comorbidities using data sources and duration of retrospective observation (6 months, 1 year, 2 years, and 3 years). The C-statistics for logistic regression and concordance index (CI) for Cox model of mortality and cardiovascular disease hospitalization were used to evaluate discrimination performance for each approach of defining comorbidities. PRINCIPAL FINDINGS: The comorbidities prevalence became higher with a longer duration. Using DAD alone underestimated the prevalence by about 75%, compared to using both DAD and physician claims. The C-statistic and CI were highest when both DAD and physician claims were used, and model performance improved when observation duration increased from 6 months to one year or longer. CONCLUSION: The comorbidities prevalence is greatly impacted by the data source and duration of retrospective observation. A combination of DAD and physicians claims with at least one year observation duration improves predictions for cardiovascular disease and one-year mortality outcome model performance. Public Library of Science 2016-09-01 /pmc/articles/PMC5008755/ /pubmed/27583532 http://dx.doi.org/10.1371/journal.pone.0162074 Text en © 2016 Chen 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Chen, Guanmin
Lix, Lisa
Tu, Karen
Hemmelgarn, Brenda R.
Campbell, Norm R. C.
McAlister, Finlay A.
Quan, Hude
Influence of Using Different Databases and ‘Look Back’ Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers
title Influence of Using Different Databases and ‘Look Back’ Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers
title_full Influence of Using Different Databases and ‘Look Back’ Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers
title_fullStr Influence of Using Different Databases and ‘Look Back’ Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers
title_full_unstemmed Influence of Using Different Databases and ‘Look Back’ Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers
title_short Influence of Using Different Databases and ‘Look Back’ Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers
title_sort influence of using different databases and ‘look back’ intervals to define comorbidity profiles for patients with newly diagnosed hypertension: implications for health services researchers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5008755/
https://www.ncbi.nlm.nih.gov/pubmed/27583532
http://dx.doi.org/10.1371/journal.pone.0162074
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