Leveraging electronic health record tools to reduce health disparities for patients with uncontrolled hypertension

三分之一的美国成年人患有高血压，但只有50%的人血压正常 控制住了。高血压在黑人成年人中的患病率是非西班牙裔白人的两倍；因此，黑人 死于高血压相关心脏病的可能性是白人的2到3倍。而当 造成这些差异的因素有很多，如缺乏强化治疗、未充分使用或处方 基于种族的口服降压药和次优的后续护理被认为是在以下背景下的中心 种族/民族差异。 健康信息技术(Health IT)解决方案，如电子健康记录中的决策支持 (EHR)系统，可以帮助缩小这些护理差距，但很少有研究评估这些系统的使用 卫生系统中照顾大量少数族裔患者的战略。同样，虽然决策支持 已经被广泛使用，但很少被用来强调护理中的种族差异，支持种族- 敏感的治疗建议，或帮助解决护理障碍，这些障碍在 少数族裔亚群。决策支持通常被用作一种单一的方法，而没有 与患者门户等其他医疗IT策略集成，以改善患者沟通。更广泛地说， 大多数工具也没有使用快速崛起的行为科学领域的原理来设计。 为此，我们提出了一个实用的随机有效性-实施混合类型2试验来测试 针对种族定制的多成分卫生信息技术干预对#年种族和民族差异的影响 高血压控制。这项试验将在Advocate Health进行，Advocate Health是 伊利诺伊州，为芝加哥地区的多种族患者人口提供服务，并拥有广泛的 有与众多学术合作伙伴进行研究研究和务实临床试验的经验。 这项研究的具体目标是：(1)设计和试点测试种族知情的卫生信息技术工具，以解决 使用患者咨询委员会和提供者焦点小组控制高血压的种族/民族差异；(2) 进行部分交叉的两臂务实整群随机试验，以确定种族- 知情的卫生信息技术工具改善了少数族裔人群的血压控制，减少了差距；以及 评估患者、提供者和诊所对卫生信息技术干预的可接受性和可采纳性， 包括干预是否减少了患者门户网站采用率的差异。 使用严格的随机设计，我们提出了一种实用且可扩展的优化方法 卫生信息技术工具，以解决差异。我们的多学科研究团队由种族/民族方面的专家组成 差异、高血压、医疗信息技术、患者和提供者行为改变，以及务实试验。预期中的 这一创新提议的总体影响是，它将从根本上推动医疗IT的优化 以可扩展并集成到医疗保健系统中的方式改善健康差距。

Hypertension affects one in three US adults, yet only 50% have their blood pressure adequately controlled. Hypertension is twice as prevalent in black adults than non-Hispanic whites; consequently, blacks are 2 to 3 times more likely to die of hypertension-related heart disease than their white counterparts. While many factors contribute to these disparities, a lack of treatment intensification, the underuse or prescribing of racially-based oral antihypertensives, and suboptimal follow-up care are thought to be central in the context of racial/ethnic disparities. Health information technology (health IT) solutions, such as decision support in electronic health record (EHR) systems, could help reduce these gaps in care, but few studies have evaluated the use of these strategies in health systems caring for a large population of minority patients. Similarly, while decision support has been widely-used, it has rarely been employed to emphasize racial differences in care, to support racially- sensitive treatment recommendations, or to help address barriers to care that are more common among minority subgroups. Decision support has generally been used as a single approach and has not been integrated with other health IT strategies like patient portals to improve patient communication. More generally, most tools have also not been designed using principles from the rapidly-emerging field of behavioral science. To this end, we propose a pragmatic randomized effectiveness-implementation hybrid type 2 trial to test the impact of a racially-tailored multicomponent health IT intervention on racial and ethnic disparities in hypertension control. This trial will be conducted at Advocate Health, the largest integrated delivery network in Illinois, which serves a multi-ethnic patient population throughout the Chicago area and has extensive experience conducting research studies and pragmatic clinical trials with numerous academic partners. The specific aims of the study are to: (1) design and pilot test racially-informed health IT tools to address racial/ethnic disparities in hypertension control using a patient advisory board and provider focus groups; (2) conduct a 2-arm pragmatic cluster randomized trial with partial crossover to determine whether racially- informed health IT tools improve blood pressure control and reduce disparities in minority populations; and (3) evaluate the acceptability and adoptability of the health IT interventions by patients, providers, and clinics, including whether the intervention reduces disparities in adoption rates of patient portals. Using a rigorous randomized design, we have proposed a pragmatic and scalable approach to optimizing health IT tools to address disparities. Our multidisciplinary study team consists of experts in racial/ethnic disparities, hypertension, health IT, patient and provider behavior change, and pragmatic trials. The expected overall impact of this innovative proposal is that it will fundamentally advance how health IT can be optimized to improve health disparities in ways that are scalable and integrated into healthcare systems.