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Thorpe LE, McVeigh KH, Perlman S, et al. Monitoring Prevalence, Treatment, and Control of Metabolic Conditions in New York City Adults Using 2013 Primary Care Electronic Health Records: A Surveillance Validation Study. EGEMS (Wash DC). 2016;4(1):1266doi: 10.13063/2327-9214.1266.
Thorpe, L. E., McVeigh, K. H., Perlman, S., Chan, P. Y., Bartley, K., Schreibstein, L., Rodriguez-Lopez, J., & Newton-Dame, R. (2016). Monitoring Prevalence, Treatment, and Control of Metabolic Conditions in New York City Adults Using 2013 Primary Care Electronic Health Records: A Surveillance Validation Study. EGEMS (Washington, DC), 4(1), 1266. https://doi.org/10.13063/2327-9214.1266
Thorpe, Lorna E, et al. "Monitoring Prevalence, Treatment, and Control of Metabolic Conditions in New York City Adults Using 2013 Primary Care Electronic Health Records: A Surveillance Validation Study." EGEMS (Washington, DC) vol. 4,1 (2016): 1266. doi: https://doi.org/10.13063/2327-9214.1266
Thorpe LE, McVeigh KH, Perlman S, Chan PY, Bartley K, Schreibstein L, Rodriguez-Lopez J, Newton-Dame R. Monitoring Prevalence, Treatment, and Control of Metabolic Conditions in New York City Adults Using 2013 Primary Care Electronic Health Records: A Surveillance Validation Study. EGEMS (Wash DC). 2016 Dec 15;4(1):1266. doi: 10.13063/2327-9214.1266. eCollection 2016. PMID: 28154836; PMCID: PMC5226388.
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EGEMS (Wash DC). 2016 Dec 15;4(1):1266. doi: 10.13063/2327-9214.1266. eCollection 2016.

Monitoring Prevalence, Treatment, and Control of Metabolic Conditions in New York City Adults Using 2013 Primary Care Electronic Health Records: A Surveillance Validation Study.

EGEMS (Washington, DC)

Lorna E Thorpe, Katharine H McVeigh, Sharon Perlman, Pui Ying Chan, Katherine Bartley, Lauren Schreibstein, Jesica Rodriguez-Lopez, Remle Newton-Dame

Affiliations

  1. NYU School of Medicine Department of Population Health.
  2. New York City Department of Health and Mental Hygiene.
  3. Formerly New York City Department of Health and Mental Hygiene.
  4. CUNY School of Public Health.

PMID: 28154836 PMCID: PMC5226388 DOI: 10.13063/2327-9214.1266

Abstract

INTRODUCTION: Electronic health records (EHRs) can potentially extend chronic disease surveillance, but few EHR-based initiatives tracking population-based metrics have been validated for accuracy. We designed a new EHR-based population health surveillance system for New York City (NYC) known as NYC Macroscope. This report is the third in a 3-part series describing the development and validation of that system. The first report describes governance and technical infrastructure underlying the NYC Macroscope. The second report describes validation methods and presents validation results for estimates of obesity, smoking, depression and influenza vaccination. In this third paper we present validation findings for metabolic indicators (hypertension, hyperlipidemia, diabetes).

METHODS: We compared EHR-based estimates to those from a gold standard surveillance source - the 2013-2014 NYC Health and Nutrition Examination Survey (NYC HANES) - overall and stratified by sex and age group, using the two one-sided test of equivalence and other validation criteria.

RESULTS: EHR-based hypertension prevalence estimates were highly concordant with NYC HANES estimates. Diabetes prevalence estimates were highly concordant when measuring diagnosed diabetes but less so when incorporating laboratory results. Hypercholesterolemia prevalence estimates were less concordant overall. Measures to assess treatment and control of the 3 metabolic conditions performed poorly.

DISCUSSION: While indicator performance was variable, findings here confirm that a carefully constructed EHR-based surveillance system can generate prevalence estimates comparable to those from gold-standard examination surveys for certain metabolic conditions such as hypertension and diabetes.

CONCLUSIONS: Standardized EHR metrics have potential utility for surveillance at lower annual costs than surveys, especially as representativeness of contributing clinical practices to EHR-based surveillance systems increases.

Keywords: Electronic health records (EHR); cardiovascular risk factors; chronic diseases; metabolic conditions; surveillance; validation

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