Affiliation: | 1. Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, Colorado;2. Department of Biostatistics and Informatics (A.M.J., M.R.), University of Colorado School of Public Health, Aurora, Colorado;3. Division of Cardiology, VA Eastern Colorado Health Care System, Aurora, Colorado;4. Department of Radiology, University of Chicago Medicine, Chicago, Illinois |
Abstract: | Observational data research studying access, utilization, cost, and outcomes of image-guided interventions using publicly available “big data” sets is growing in the interventional radiology (IR) literature. Publicly available data sets offer insight into real-world care and represent an important pillar of IR research moving forward. They offer insights into how IR procedures are being used nationally and whether they are working as intended. On the other hand, large data sources are aggregated using complex sampling frames, and their strengths and weaknesses only become apparent after extensive use. Unintentional misuse of large data sets can result in misleading or sometimes erroneous conclusions. This review introduces the most commonly used databases relevant to IR research, highlights their strengths and limitations, and provides recommendations for use. In addition, it summarizes methodologic best practices pertinent to all data sets for planning and executing scientifically rigorous and clinically relevant observational research. |