Abstract 332: Toward Big Data: Integrating Cardiovascular Registry and Claims Data to Create a Clinical Practice-based Analytical Platform

Background: There is great promise in ‘big data’ analytics that leverage multiple data sources including clinical registries and claims data, creating large, broadly distributed, and clinically detailed analytical platforms to study a range of cardiovascular topics, including practice patterns associated with optimal clinical outcomes. Objective: Describe a newly created integrated analytical platform utilizing U.S. cardiovascular registry records and healthcare claims data from real-world clinical practices. Methods: The analytical platform includes records from five American College of Cardiology (ACC) National Cardiovascular Data Registry programs and pharmacy, private practitioner and hospital claims data from Symphony Health Solutions (SHS). The NCDR registries include ≈ 650,000 patients in ACTION Registry-GWTG (acute coronary syndrome), 6.7m in CathPCI (diagnostic cardiac catheterizations and PCI), 660,000 in ICD (implantable cardioverter defibrillators), 33,000 in IMPACT (pediatric and adult congenital treatment) and 3.4m in PINNACLE (ambulatory CAD, HTN, HF and AFib). With history as early as 2003, SHS currently receives one or more pharmacy, practitioner or hospital claims annually for ≈274m patients in the U.S. All payer types are represented, including self-pay pharmacy patients. Patient inclusion criteria: 1) Data within 2006 [[Unable to Display Character: –]] 2014, 2) one or more records in ≥ 1 of 5 NCDR registries, 3) one or more claims observed in ≥ 1 of 3 SHS datasets: pharmacy, private practitioner or hospital claims, 4) populated data fields enabling generation of a unique, patient-level, synthetic identifier (ID) for matching and longitudinal linkage across the registry(s) and the dataset(s). The analytical platform has been developed using a HIPAA and HITECH compliant, certified approach. Results: Over 8.7 million patients have been successfully linked between the NCDR registries and the SHS claims data. On average, 95% of patients in the registry(s) sample was also observed and matched in the SHS datasets. Conclusion: High match rates were observed between the ACC and SHS data, identifying large populations of patients with cardiovascular disease. Clinical registry data combined with longitudinal claims data will generate a ‘broad’ and ‘deep’ data platform for analytics of quality of care and outcomes.