Utilizing Combined Claims and Clinical Datasets for Research Among Potential Cases of Rare Diseases

Kevin J. Bennett, Joshua Mann and Lijing Ouyang
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Kevin J. Bennett: University of South Carolina, Columbia, SC, USA
Joshua Mann: University of Mississippi Medical Center, Jackson, MS, USA
Lijing Ouyang: Centers for Disease Control & Prevention, Atlanta, GA, USA

International Journal of Healthcare Information Systems and Informatics (IJHISI), 2018, vol. 13, issue 2, 1-12

Abstract: With data quality issues with administrative claims and medically derived datasets, a dataset derived from a combination of sources may be more effective for research. The purposes of this article is to link an EMR-based data warehouse with state administrative data to study individuals with rare diseases; to describe and compare their characteristics; and to explore research with the data. These methods included subjects with diagnosis codes for one of three rare diseases from the years 2009-2014; Spina Bifida, Muscular Dystrophy, and Fragile X Syndrome. The results from the combined data provides additional information that each dataset, by itself, would not contain. The simultaneous examination of data such as race/ethnicity, physician and other outpatient visit data, charges and payments, and overall utilization was possible in the combined dataset. It is also discussed that combining such datasets can be a useful tool for the study of populations with rare diseases.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jhisi0:v:13:y:2018:i:2:p:1-12

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