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American Journal of Public Health
Article . 2017 . Peer-reviewed
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Innovations in Population Health Surveillance: Using Electronic Health Records for Chronic Disease Surveillance

Authors: Sharon E, Perlman; Katharine H, McVeigh; Lorna E, Thorpe; Laura, Jacobson; Carolyn M, Greene; R Charon, Gwynn;

Innovations in Population Health Surveillance: Using Electronic Health Records for Chronic Disease Surveillance

Abstract

With 87% of providers using electronic health records (EHRs) in the United States, EHRs have the potential to contribute to population health surveillance efforts. However, little is known about using EHR data outside syndromic surveillance and quality improvement. We created an EHR-based population health surveillance system called the New York City (NYC) Macroscope and assessed the validity of diabetes, hyperlipidemia, hypertension, smoking, obesity, depression, and influenza vaccination indicators. The NYC Macroscope uses aggregate data from a network of outpatient practices. We compared 2013 NYC Macroscope prevalence estimates with those from a population-based, in-person examination survey, the 2013–2014 NYC Health and Nutrition Examination Survey. NYC Macroscope diabetes, hypertension, smoking, and obesity prevalence indicators performed well, but depression and influenza vaccination estimates were substantially lower than were survey estimates. Ongoing validation will be important to monitor changes in validity over time as EHR networks mature and to assess new indicators. We discuss NYC’s experience and how this project fits into the national context. Sharing lessons learned can help achieve the full potential of EHRs for population health surveillance.

Keywords

Inventions, Primary Health Care, Population Surveillance, Chronic Disease, Prevalence, Electronic Health Records, Humans, Female, New York City, Nutrition Surveys

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
56
Top 10%
Top 10%
Top 10%
bronze