title: Administrative Databases in Orthopaedic Research: Pearls and Pitfalls of Big Data.
abstract: The drive for evidence-based decision-making has highlighted the shortcomings of traditional orthopaedic literature. Although high-quality, prospective, randomized studies in surgery are the benchmark in orthopaedic literature, they are often limited by size, scope, cost, time, and ethical concerns and may not be generalizable to larger populations. Given these restrictions, there is a growing trend toward the use of large administrative databases to investigate orthopaedic outcomes. These datasets afford the opportunity to identify a large numbers of patients across a broad spectrum of comorbidities, providing information regarding disparities in care and outcomes, preoperative risk stratification parameters for perioperative morbidity and mortality, and national epidemiologic rates and trends. Although there is power in these databases in terms of their impact, potential problems include administrative data that are at risk of clerical inaccuracies, recording bias secondary to financial incentives, temporal changes in billing codes, a lack of numerous clinically relevant variables and orthopaedic-specific outcomes, and the absolute requirement of an experienced epidemiologist and/or statistician when evaluating results and controlling for confounders. Despite these drawbacks, administrative database studies are fundamental and powerful tools in assessing outcomes on a national scale and will likely be of substantial assistance in the future of orthopaedic research.
authors.affiliation: From Northwestern University Feinberg School of Medicine (Dr. Patel) and Rush University (Dr. Singh), Chicago, IL, Washington University, St. Louis, MO (Dr. Nunley), and NYU Hospital for Joint Diseases, New York, NY (Dr. Minhas).
authors.forename: Alpesh A
authors.initials: AA
authors.lastname: Patel
authors.forename: Kern
authors.initials: K
authors.lastname: Singh
authors.forename: Ryan M
authors.initials: RM
authors.lastname: Nunley
authors.forename: Shobhit V
authors.initials: SV
authors.lastname: Minhas
mesh_terms: D035843:Biomedical Research / Q000592:standards*; D066264:Datasets as Topic / Q000592:standards*; D019317:Evidence-Based Medicine / Q000592:standards; D006801:Humans; D009985:Orthopedics / Q000592:standards*