Improving the geographical precision of rural chronic disease surveillance by using emergency claims data: a cross-sectional comparison of survey versus claims data in Sullivan County, New York.

Objectives Some of the most pressing health problems are found in rural America. However, the surveillance needed to track and prevent disease in these regions is lacking. Our objective was to perform a comprehensive health survey of a single rural county to assess the validity of using emergency claims data to estimate rural disease prevalence at a sub-county level. Design We performed a cross-sectional study of chronic disease prevalence estimates using emergency department (ED) claims data versus mailed health surveys designed to capture a substantial proportion of residents in New York's rural Sullivan County. Setting Sullivan County, a rural county ranked second-to-last for health outcomes in New York State. Participants Adult residents of Sullivan County aged 25 years and older who responded to the health survey in 2017-2018 or had at least one ED visit in 2011-2015. Outcome measures We compared age and gender-adjusted prevalence of hypertension, hyperlipidaemia, diabetes, cancer, asthma and chronic obstructive pulmonary disease/emphysema among nine sub-county areas. Results Our county-wide mailed survey obtained 6675 completed responses for a response rate of 30.4%. This sample represented more than 12% of the estimated 53 020 adults in Sullivan County. Using emergency claims data, we identified 34 576 adults from Sullivan County who visited an ED at least once during 2011-2015. At a sub-county level, prevalence estimates from mailed surveys and emergency claims data correlated especially well for diabetes (r=0.90) and asthma (r=0.85). Other conditions were not well correlated (range: 0.23-0.46). Using emergency claims data, we created more geographically detailed maps of disease prevalence using geocoded addresses. Conclusions For select conditions, emergency claims data may be useful for tracking disease prevalence in rural areas and providing more geographically detailed estimates. For rural regions lacking robust health surveillance, emergency claims data can inform how to geographically target efforts to prevent chronic disease.