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Bridging the gap between clinical practice and public health: Using EHR data to assess trends in the seasonality of blood-pressure control()

Electronic health records (EHRs) provide timely access to millions of patient data records while limiting errors associated with manual data extraction. To demonstrate these advantages of EHRs to public health practice, we examine the ability of a EHR calculated blood-pressure (BP) measure to replic...

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Autores principales: Amoah, Aurora O., Angell, Sonia Y., Byrnes-Enoch, Hannah, Amirfar, Sam, Maa, Phoenix, Wang, Jason J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5443962/
https://www.ncbi.nlm.nih.gov/pubmed/28593116
http://dx.doi.org/10.1016/j.pmedr.2017.04.007
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author Amoah, Aurora O.
Angell, Sonia Y.
Byrnes-Enoch, Hannah
Amirfar, Sam
Maa, Phoenix
Wang, Jason J.
author_facet Amoah, Aurora O.
Angell, Sonia Y.
Byrnes-Enoch, Hannah
Amirfar, Sam
Maa, Phoenix
Wang, Jason J.
author_sort Amoah, Aurora O.
collection PubMed
description Electronic health records (EHRs) provide timely access to millions of patient data records while limiting errors associated with manual data extraction. To demonstrate these advantages of EHRs to public health practice, we examine the ability of a EHR calculated blood-pressure (BP) measure to replicate seasonal variation as reported by prior studies that used manual data extraction. Our sample included 609 primary-care practices in New York City. BP control among hypertensives was defined as systolic blood pressure of 140 or less and diastolic blood pressure of 90 or less (BP < 140/90 mm Hg). An innovative query-distribution system was used to extract monthly BP control values from the EHRs of adult patients diagnosed with hypertension over a 25-month period. Generalized estimating equations were used to compare the association between seasonal temperature variations and BP control rates at the practice level, while adjusting for known demographic factors (age, gender), comorbid diseases (diabetes) associated with blood pressure, and months since EHR implementation. BP control rates increased gradually from the spring months to peak summer months before declining in the fall months. In addition to seasonal variation, the adjusted model showed that a 1% increase in patients with a diabetic comorbidity is associated with an increase of 3% (OR 1.03; CI 1.028–1.032) on the BP measure. Our findings identified cyclic trends in BP control and highlighted greater association with increased proportion of diabetic patients, therefore confirming the ability of the EHR as a tool for measuring population health outcomes.
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spelling pubmed-54439622017-06-07 Bridging the gap between clinical practice and public health: Using EHR data to assess trends in the seasonality of blood-pressure control() Amoah, Aurora O. Angell, Sonia Y. Byrnes-Enoch, Hannah Amirfar, Sam Maa, Phoenix Wang, Jason J. Prev Med Rep Regular Article Electronic health records (EHRs) provide timely access to millions of patient data records while limiting errors associated with manual data extraction. To demonstrate these advantages of EHRs to public health practice, we examine the ability of a EHR calculated blood-pressure (BP) measure to replicate seasonal variation as reported by prior studies that used manual data extraction. Our sample included 609 primary-care practices in New York City. BP control among hypertensives was defined as systolic blood pressure of 140 or less and diastolic blood pressure of 90 or less (BP < 140/90 mm Hg). An innovative query-distribution system was used to extract monthly BP control values from the EHRs of adult patients diagnosed with hypertension over a 25-month period. Generalized estimating equations were used to compare the association between seasonal temperature variations and BP control rates at the practice level, while adjusting for known demographic factors (age, gender), comorbid diseases (diabetes) associated with blood pressure, and months since EHR implementation. BP control rates increased gradually from the spring months to peak summer months before declining in the fall months. In addition to seasonal variation, the adjusted model showed that a 1% increase in patients with a diabetic comorbidity is associated with an increase of 3% (OR 1.03; CI 1.028–1.032) on the BP measure. Our findings identified cyclic trends in BP control and highlighted greater association with increased proportion of diabetic patients, therefore confirming the ability of the EHR as a tool for measuring population health outcomes. Elsevier 2017-04-26 /pmc/articles/PMC5443962/ /pubmed/28593116 http://dx.doi.org/10.1016/j.pmedr.2017.04.007 Text en © 2017 Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Amoah, Aurora O.
Angell, Sonia Y.
Byrnes-Enoch, Hannah
Amirfar, Sam
Maa, Phoenix
Wang, Jason J.
Bridging the gap between clinical practice and public health: Using EHR data to assess trends in the seasonality of blood-pressure control()
title Bridging the gap between clinical practice and public health: Using EHR data to assess trends in the seasonality of blood-pressure control()
title_full Bridging the gap between clinical practice and public health: Using EHR data to assess trends in the seasonality of blood-pressure control()
title_fullStr Bridging the gap between clinical practice and public health: Using EHR data to assess trends in the seasonality of blood-pressure control()
title_full_unstemmed Bridging the gap between clinical practice and public health: Using EHR data to assess trends in the seasonality of blood-pressure control()
title_short Bridging the gap between clinical practice and public health: Using EHR data to assess trends in the seasonality of blood-pressure control()
title_sort bridging the gap between clinical practice and public health: using ehr data to assess trends in the seasonality of blood-pressure control()
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5443962/
https://www.ncbi.nlm.nih.gov/pubmed/28593116
http://dx.doi.org/10.1016/j.pmedr.2017.04.007
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