TY - JOUR
T1 - Determining chronic disease prevalence in local populations using emergency department surveillance
AU - Lee, David C.
AU - Long, Judith A.
AU - Wall, Stephen P.
AU - Carr, Brendan G.
AU - Satchell, Samantha N.
AU - Braithwaite, R. Scott
AU - Elbel, Brian
PY - 2015/9/1
Y1 - 2015/9/1
N2 - Objectives. We sought to improve public health surveillance by using a geographic analysis of emergency department (ED) visits to determine local chronic disease prevalence. Methods. Using 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. Results. We identified 4.4 million unique New York City adults visiting an ED between 2009 and 2012.Whenwe 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. Conclusions. Our 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.
AB - Objectives. We sought to improve public health surveillance by using a geographic analysis of emergency department (ED) visits to determine local chronic disease prevalence. Methods. Using 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. Results. We identified 4.4 million unique New York City adults visiting an ED between 2009 and 2012.Whenwe 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. Conclusions. Our 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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U2 - 10.2105/AJPH.2015.302679
DO - 10.2105/AJPH.2015.302679
M3 - Article
C2 - 26180983
AN - SCOPUS:84939136379
SN - 0090-0036
VL - 105
SP - e67-e74
JO - American journal of public health
JF - American journal of public health
IS - 9
ER -