Center, Fairbanks, AK, 3Harvard University Medical School and Harvard. Pilgrim Health Care Institute, Boston, MA. INTRODUCTION: In the United States, the ...
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Poster Number: W61 Abstract #: 3921 Improving Access to Affordable Care Act Health Insurance in Alaska using Geographical Cluster Detection of the Uninsured. P. Amstislavski, PhD1,2 and M. Kulldorff, PhD3 1
University of Alaska Fairbanks, Fairbanks, AK, 2Fairbanks Public Health Center, Fairbanks, AK, 3Harvard University Medical School and Harvard Pilgrim Health Care Institute, Boston, MA INTRODUCTION: In the United States, the Affordable Care Act (ACA) health insurance reform was conceived to improve access to health care for the uninsured. Open enrollment into the ACA coverage began on 1 October 2013 and ends on 31 March 31 2014. This timeframe imparts urgency to providing enrollment information and assistance to communities with high rates of the uninsured. Due to complexity of the ACA insurance application process, making informed decision about enrollment and completing the application often requires assistance from a trained ACA navigator. In rural Alaska the shortage of trained ACA navigators makes it necessary to prioritize their visits to assist with the enrollment to areas with large concentrations of the uninsured. The objective of this study is to analyze geo-referenced health insurance data at the census tract level for presence of spatial clusters of uninsured to guide efforts to maximize the sparse resources available to increase health insurance rates in Alaska. METHODS: Health insurance status for non-institutionalized population aged 18–64 at the US Census tract level for Alaska (n ¼ 167) was determined using the American Community Survey estimates data. The spatial scan statistic in the free SaTScan software was used to detect statistically significant geographical clusters of uninsured, adjusting for the multiple testing inherent in many potential cluster sizes and locations. RESULTS: Rates of Alaskans aged 18–64 without health insurance varied greatly along the urban-to-rural gradient (1.9–70.2%). Remote, rural geographically isolated census tracts had the highest rate of uninsured individuals. The mapped clusters will be used to guide ACA coverage enrollment activities until the end of the open enrollment in March 2014. Full results will be available at that time. CONCLUSIONS: Spatial cluster scan statistics can be applied to guide health insurance navigators to specific geographic areas with large uninsured populations to increase health insurance rates in Alaska.
International Journal of Epidemiology, 2015, Vol. 44, Supplement 1
