OBJECTIVES: As outcomes research methodologies advance, they should increasingly allow access by different disciplines as clinicians, epidemiologists, economists, and statisticians interact frequently. A data visualization tool can present complex patterns effectively to a diverse audience. The objective of this study was to present treatment patterns among Veterans Health Administration (VHA) patients diagnosed with ankylosing spondylitis (AS) using advanced data visualization techniques. METHODS: Using the VHA Medical SAS®dataset, adult patients with at least one AS diagnosis (ICD-9-CM: 720.0) were selected. Prescriptions for anti-tumor necrosis factor (anti-TNF) and non-TNF agents were identified. For 2 years after the date of the first prescription (initiation date), drug switches and discontinuation were examined. Using a processing language, a data visualization tool was developed to demonstrate changes in treatment patterns after the first and second treatment switches. RESULTS: A total of 1,021 AS patients initiated therapy with TNF, of which 13.52% switched to another TNF, 0.20% switched to a non-TNF, 49.56% discontinued therapy and 36.73% continued their initial therapy. Among patients who switched to another TNF, 60.87% remained on the switched therapy, while 31.16% discontinued therapy, 7.97% switched to another TNF, and no patients switched to a non-TNF. 81.82% of patients who made a second switch to a TNF medication remained on this TNF, while 9.09% discontinued treatment. A total of 84 AS patients initiated therapy with a non-TNF. 4.76% of these patients switched to a TNF, 1.19% switched to another non-TNF, 93.61% discontinued therapy and no patients continued treatment. Of those patients whose first switch was to a TNF, 50% continued therapy while the remaining 50% discontinued. There were no second switches. CONCLUSIONS: When analyzing several years of data including treatment (dis)continuation and switches, treatment patterns can be difficult to capture. Data visualization tools help present complicated flows effectively for a diverse research audience.