• Am J Public Health · Sep 2015

    Determining Chronic Disease Prevalence in Local Populations Using Emergency Department Surveillance.

    • David C Lee, Judith A Long, Stephen P Wall, Brendan G Carr, Samantha N Satchell, R Scott Braithwaite, and Brian Elbel.
    • David C. Lee and Stephen P. Wall are with the Ronald O. Perelman Department of Emergency Medicine and R. Scott Braithwaite and Brian Elbel are with the Department of Population Health, New York University School of Medicine, New York, NY. Judith A. Long is with the Center for Health Equity Research and Promotion, Philadelphia Veterans Affairs Medical Center, Philadelphia, PA. Brendan G. Carr is with the Department of Emergency Medicine, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA. Samantha N. Satchell is with the Milken Institute School of Public Health, George Washington University, Washington, DC.
    • Am J Public Health. 2015 Sep 1;105(9):e67-74.

    ObjectivesWe sought to improve public health surveillance by using a geographic analysis of emergency department (ED) visits to determine local chronic disease prevalence.MethodsUsing an all-payer administrative database, we determined the proportion of unique ED patients with diabetes, hypertension, or asthma. We compared these rates to those determined by the New York City Community Health Survey. For diabetes prevalence, we also analyzed the fidelity of longitudinal estimates using logistic regression and determined disease burden within census tracts using geocoded addresses.ResultsWe identified 4.4 million unique New York City adults visiting an ED between 2009 and 2012. When we compared our emergency sample to survey data, rates of neighborhood diabetes, hypertension, and asthma prevalence were similar (correlation coefficient = 0.86, 0.88, and 0.77, respectively). In addition, our method demonstrated less year-to-year scatter and identified significant variation of disease burden within neighborhoods among census tracts.ConclusionsOur method for determining chronic disease prevalence correlates with a validated health survey and may have higher reliability over time and greater granularity at a local level. Our findings can improve public health surveillance by identifying local variation of disease prevalence.

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