Rare Condition Research Using a Combined Administrative/Clinical Data Warehouse

Kevin Bennett, PhD, Principal Investigator, University of South Carolina. (Funded 2014-2017) We propose to use administrative data and information from electronic medical records to identify and describe individuals living in South Carolina who have spina bifida, muscular dystrophy, or fragile x syndrome. In years 2 and 3 of the project, we will conduct research in collaboration with CDC staff, to answer important questions about the health of people with these conditions. For the proposed project, we will obtain linked data from the South Carolina Division of Research and Statistics, to include billing records from Medicaid, the State Health Plan, and the Uniform Billing 04 that captures billing to any payer for emergency department visits and hospitalizations. We will also obtain vital records (death certificates) data from the Division of Research and Statistics. Electronic medical record data will be obtained from Health Sciences of South Carolina, which was established in 2004 as the nation’s first statewide biomedical research collaborative. Its members include six of the state’s largest health systems (Greenville Hospital System, University Medical Center, Palmetto Health, Spartanburg Regional Healthcare System, McLeod Health, AnMed Health, and Self Regional Healthcare) and the state’s largest research-intensive universities (Clemson University, the Medical University of South Carolina, and the University of South Carolina). We will obtain clinical data for individuals with one of the three conditions, receiving treatment from participating health systems. This data set will then be provided to the Division of Research and Statistics, where staff will link it to the sate data sources housed there to create a merged data set for analyses. We will use this data set to characterize the individuals with each of the three rare conditions identified in each data set, and those identified in both. We will work with CDC staff to develop one or more research questions to answer with the data and to conduct research to answer those questions.