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

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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)

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.

Suggested Citation

  • Kevin J. Bennett & Joshua Mann & Lijing Ouyang, 2018. "Utilizing Combined Claims and Clinical Datasets for Research Among Potential Cases of Rare Diseases," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 13(2), pages 1-12, April.
  • Handle: RePEc:igg:jhisi0:v:13:y:2018:i:2:p:1-12
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