AB0861 METHODS TO EFFICIENTLY RECRUIT MINORITY PATIENTS WITH GOUT FOR CLINIC-BASED REGISTRIES
Authors: Giovanni Adami, Josh Melnick, Jeff Foster, Elizabeth Rahn, Amy Mudano, Jeffrey Curtis, Tony Merriman, Lou Bridges, Kenneth Saag
Journal: Annals of the Rheumatic Diseases (2019)

<h3>Background</h3> Gout is frequently misdiagnosed and/or miscoded, making approaches to identifying eligible patients for observational and interventional studies more challenging. Ethnic and racial minorities are under-represented in many gout studies. Methods to better identify minorities and confirm gout diagnosis are essential to ensure studies have both validity and generalizability. <h3>Objectives</h3> To define efficient methods for identifying African Americans (AA) interested in participating in a gout registry and who satisfy the American College of Rheumatology (ACR) and European League Against Rheumatism (EULAR) gout classification criteria. <h3>Methods</h3> We identified all AA patients seen at University of Alabama at Birmingham 01/09/2017 and 31/08/2018 with an ICD 9/10 code for gout. Patients not "opted out" by their primary care provider (PCP) were invited to participate. Those interested underwent detailed medical record review followed by phone contact to determine eligibility. Those with a high likelihood of meeting diagnostic criteria for gout were invited for an in person visit to confirm diagnosis (Abstract AB0861 Figure 1). We compared descriptive characteristic of participants enrolled in the registry and the larger potential gout populations <h3>Results</h3> From 3,032 AA patients with an ICD 9/10 gout diagnosis we generated a random sample of 400 patients. 5 patients were excluded by their PCPs, thus 395 patients were preliminarily eligible and invited via e-mail (N=176) and/or letter (N=375). 1 patient (&lt; 1%) communicated lack of interest, 19 (4.8%) were unreachable, 322 (81.5%) did not respond to the invitation, and 53 (13.4%) expressed preliminary interest and underwent medical record review. We successfully scheduled 30 subjects for a registry visit, 24 completed the visit, and 23 (6% of initial sample) satisfied 2015 ACR/EULAR gout classification criteria (see <b>Table 1</b>). We found no significant difference in age, sex, and the number of medical encounters in the last year between enrolled patients and the remaining population. <h3>Conclusion</h3> We present a strategy for identifying and recruiting AA patients with ACR/EULAR classified gout into a population-based registry. Among a randomly selected cohort of AAs with an initial ICD 9/10 diagnosis code of presumed gout, slightly under 15% expressed interest and 6% satisfied the 2015 ACR/EULAR criteria and successfully enrolled in the registry. Our experience emphasizes a potential approach as well as some challenges in creating a generalizable gout registry. <h3>Disclosure of Interests</h3> Giovanni Adami: None declared, Josh Melnick: None declared, Jeff Foster: None declared, Elizabeth Rahn: None declared, Amy Mudano: None declared, Jeffrey Curtis: None declared, Tony Merriman Grant/research support from: Ardeabiosciences, Ironwood Pharmaceuticals, Consultant for: Ardeabiosciences, Ironwood Pharmaceuticals, Lou Bridges: None declared, Kenneth Saag Grant/research support from: Amgen, Ironwood/AstraZeneca, Horizon, SOBI, Takeda, Consultant for: Abbvie, Amgen, Ironwood/AstraZeneca, Bayer, Gilead, Horizon, Kowa, Radius, Roche/Genentech, SOBI, Takeda, Teijin