Construction of an Administrative Osteoarthritis Severity Index

Abstract

Objective Electronic health record (EHR) databases are a powerful resource to investigate clinical trajectories of osteoarthritis (OA). There are no existing EHR tools to evaluate risk for knee arthroplasty (KA). We developed an OA severity index (OASI) using EHR data and demonstrate the index's association with time to KA. Methods This retrospective cohort study used 2010‐2018 nationally distributed Optum EHR data. Eligible patients were 45 to 80 years old with a new diagnosis of knee OA in 2011‐2012 and no prior KA. The OASI was a sum of first instance of x‐ray imaging, advanced imaging, intra‐articular injection, nonsteroidal anti‐inflammatory drugs, and opioids. Principal components analysis index (PCI) score was also explored. Extended Cox proportional hazard models assessed time‐dependent OASI and time to KA. Results Among 16,675 eligible patients, 12.7% underwent KA. Median follow‐up time was 72 months. Adjusted OASI models showed each additional event almost doubled the risk for KA (adjusted hazard ratio = 1.80, 95% confidence interval: 1.75‐1.86). Similar results were observed for PCI. Conclusion The sum OASI performs well identifying patients who would undergo KA and offers simplicity versus the PCI. Although replication in other cohorts is recommended, the OASI appears to be a novel and valid means to measure clinical OA severity in research studies using large EHR‐based cohorts.