Population-Based Outcomes Research for Rheumatoid Arthritis: Rural Health Disparities

项目总结/摘要 在类风湿性关节炎（RA）中，延迟开始治疗≥12周与不可逆关节炎相关。 由于更难实现缓解而造成的损害，但要克服美国医疗保健系统的障碍， 在这么短的时间内完成任务是很有挑战性的。必须进行耗时的后勤步骤以进行评估 由合格的专家，建立诊断，并开始抗风湿药物治疗。这些困难 由于全国农村医院关闭，农村居民的病情加剧， 医疗保健设施和旅行和获得护理的时间。此外，关于这方面的信息很少。 RA诊断的时间和准确性及其对美国农村居民结局的相关影响。的 日益严重的风湿病学劳动力短缺进一步加剧了这些问题，因为<10%的风湿病学专家 在农村或小城市地区，30%的美国人口生活在这些地区。我们的目标是改善结果 在RA患者中，通过减少医疗保健差异。我们的目标是（1）确定农村医疗保健差距， 早期RA的诊断和治疗，（2）开发和验证AI算法，以实现早期识别 （3）评估生活在农村与城市地区的RA患者的长期结局， 没有RA。 我们在实现这些目标方面具有独特的优势，因为我们是唯一一家以人口为基础的纵向RA 我们将把我们的队列扩展到扩大的罗切斯特流行病学项目 集水区，包括MN和WI的27个城乡混合县（60%为农村）。其中，农村73 在过去5年中关闭了17个医疗设施的社区。另外，我们有唯一的井- 与事件RA患者的策划数据库，因为我们手动筛选所有潜在的RA病例，以确保他们 美国流变学学会/欧洲流变学协会联盟 (ACR/EULAR）RA的分类标准。这对RA研究至关重要，因为 RA（尤其是血清阴性RA）通常不准确。这项研究将提供关于以下方面的真实证据： 农村类风湿性关节炎患者的医疗保健差异程度。我们的AI算法有助于早期识别 将通过以下三个有意义的方式改善临床实践：1）减少农村RA的诊断不足 初级保健机构，2）促进及时开始抗风湿治疗，以减少关节损伤， 改善长期结果，3）优化转介到风湿病学专业护理，以减少 劳动力短缺。这项工作将是一个务实的临床试验测试的发展基础 实施临床决策支持工具，以减少RA早期识别的差异。此外，委员会认为， 评估长期结果并确定具有最差结果的患者亚组是重要的一步 以制定干预措施来弥合医疗保健服务中的这些差距。

PROJECT SUMMARY/ABSTRACT In rheumatoid arthritis (RA), delaying initiation of treatment for ≥12 weeks is associated with irreversible joint damage due to greater difficulty in achieving remission, but navigating the hurdles of the US healthcare system in this short timeframe can be challenging. Time-consuming logistical steps must be carried out to be evaluated by a qualified specialist, establish a diagnosis, and start antirheumatic drug therapy. These difficulties are exacerbated for rural residents due to the closure of rural hospitals nationwide extending the distance to healthcare facilities and the time to travel and obtain care. Additionally, there is very little information about the timing and accuracy of RA diagnosis and their associated effects on outcomes for rural residents of the US. The growing rheumatology workforce shortage further aggravates these issues, as <10% of rheumatologists practice in rural or micropolitan areas yet 30% of the US population lives in these areas. Our goal is to improve outcomes in patients with RA by reducing healthcare disparities. Our aims are to (1) identify rural healthcare disparities in diagnosis and treatment of early RA, (2) to develop and validate an AI algorithm to enable early identification of RA, and (3) to assess long-term outcomes in patients with RA living in rural vs urban areas compared to those without RA. We are uniquely positioned to address these objectives as ours is the only population-based, longitudinal RA inception cohort in the US, and we will extend our cohort to the expanded Rochester Epidemiology Project catchment area, comprising 27 mixed rural-urban counties in MN and WI (60% rural). This area includes 73 rural communities where 17 medical facilities have closed in the past 5 years. In addition, we have the only well- curated database of patients with incident RA, as we manually screen all potential cases of RA to ensure they meet the American College of Rheumatology/ European Alliance of Associations for Rheumatology (ACR/EULAR) classification criteria for RA. This is essential for RA research because the diagnostic codes for RA (especially seronegative RA) are often inaccurate. This research will provide real-world evidence regarding the magnitude of healthcare disparities in rural residents with RA. Our AI algorithm to facilitate early recognition of RA will improve clinical practice in three meaningful ways, by: 1) reducing underdiagnosis of RA in rural primary care settings, 2) facilitating timely initiation of anti-rheumatic therapies to reduce joint damage and improve long-term outcomes, and 3) optimizing referrals to rheumatology specialty care to reduce the impact of the workforce shortage. This work will be foundational for the development of a pragmatic clinical trial testing implementation of a clinical decision support tool to reduce disparities in early identification of RA. Furthermore, evaluating long-term outcomes and identifying patient subgroups with the worst outcomes is an important step toward developing interventions to bridge these gaps in healthcare delivery.