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

To determine the data sources and 'look back' intervals to define comorbidities.Hospital discharge abstracts database (DAD), physician claims, population registry and death registry from April 1, 1994 to March 31, 2010 in Alberta, Canada.Newly-diagnosed hypertension cases from 1997 to 2008...

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Main Authors: Guanmin Chen, Lisa Lix, Karen Tu, Brenda R Hemmelgarn, Norm R C Campbell, Finlay A McAlister, Hude Quan, Hypertension Outcome and Surveillance Team
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5008755?pdf=render
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spelling doaj-f0babad73c5b4e5ea706ac08081620742020-11-24T20:45:28ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01119e016207410.1371/journal.pone.0162074Influence of Using Different Databases and 'Look Back' Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers.Guanmin ChenLisa LixKaren TuBrenda R HemmelgarnNorm R C CampbellFinlay A McAlisterHude QuanHypertension Outcome and Surveillance TeamTo determine the data sources and 'look back' intervals to define comorbidities.Hospital discharge abstracts database (DAD), physician claims, population registry and death registry from April 1, 1994 to March 31, 2010 in Alberta, Canada.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.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.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.http://europepmc.org/articles/PMC5008755?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Guanmin Chen
Lisa Lix
Karen Tu
Brenda R Hemmelgarn
Norm R C Campbell
Finlay A McAlister
Hude Quan
Hypertension Outcome and Surveillance Team
spellingShingle Guanmin Chen
Lisa Lix
Karen Tu
Brenda R Hemmelgarn
Norm R C Campbell
Finlay A McAlister
Hude Quan
Hypertension Outcome and Surveillance Team
Influence of Using Different Databases and 'Look Back' Intervals to Define Comorbidity Profiles for Patients with Newly Diagnosed Hypertension: Implications for Health Services Researchers.
PLoS ONE
author_facet Guanmin Chen
Lisa Lix
Karen Tu
Brenda R Hemmelgarn
Norm R C Campbell
Finlay A McAlister
Hude Quan
Hypertension Outcome and Surveillance Team
author_sort Guanmin Chen
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_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_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_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.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description To determine the data sources and 'look back' intervals to define comorbidities.Hospital discharge abstracts database (DAD), physician claims, population registry and death registry from April 1, 1994 to March 31, 2010 in Alberta, Canada.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.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.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.
url http://europepmc.org/articles/PMC5008755?pdf=render
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