Objectives: Biologic disease modifying anti-rheumatic drugs (bDMARDs) are the cornerstone of active rheumatoid arthritis (RA) treatment when traditional DMARDs are no longer effective. The objective of this study is to evaluate recent real-world treatment choices and switching in the US. MethOds: Patients initiating a bDMARD for RA between 10/2015-09/2016 were identified from the Symphony Health claims database. A minimum age of 18 years and 6 months of pre-and post-initiation medical and pharmacy claims activity was required. The study examined market share among biologic starts and switching patterns. Results: In the 12-month period, 19,288 patients initiated a new biologic: 15,337 (79.5%) were female, mean (SD) age was 54.7 (12.9) years, mean (SD) number of biologics was 1.4 (0.7). The top 3 biologics were: adalimumab (5,824; 28.8%), etanercept (5,817; 28.8%), abatacept (2,013; 10.0%). For 16,301 patients on first biologic, the top 3 biologics were: etanercept (5,203; 31.9%), adalimumab (5,010; 30.7%), infliximab (1,496; 9.2%); for 3,042 patients on second biologic, top 3 biologics were adalimumab (742; 24.4%), etanercept (564; 18.5%), tofacitinib citrate (429; 14.1%); for 865 patients on third biologic or more, top 3 biologics were tofacitinib (207; 23.9%), abatacept (172; 19.9%), tocilizumab (154; 17.8%). Tumor-necrosis factor inhibitors (TNFi) were used in 77.9% of first-line, 67.0% of second-line, and 62.0% of third-line or higher therapies. Of 3,913 switchers, 30.5% switched from etanercept (48.4% to adalimumab), 28.6% switched from adalimumab (38.7% to etanercept), and 10.9% switched from abatacept (25.4% to tocilizumab, 24.5% tofacitinib) with mean (SD) time to switch of 345.5 (132.7), 334.1 (152.3), and 338.3 (149.1) days respectively. cOnclusiOns: RA patients receive multiple lines of bDMARD therapy. Despite availability of drugs with alternative mechanisms of action, TNFi are preferred agents with adalimumab and etanercept dominating as first and second biologics. Comparative effectiveness research is needed to evaluate optimal sequencing.