Identifying Risk Factors for Poor Glycemic Control among Emergency Department Patients and Improving Linkage to Outpatient Care

项目总结 在每年去急诊室就诊的数百万美国人中，有更高的 种族和少数民族以及有显著社会经济障碍的患者中使用ED的比率。 然而，急诊室很少提供任何形式的预防性护理，而且他们提供的护理往往不是很好 与极其重要的门诊护理相协调。其后果是更高的未诊断率 ED患者中的糖尿病等疾病，然后得不到治疗，加剧了健康差距，穷人 血糖控制、糖尿病并发症和糖尿病相关早期死亡。考虑到边缘的高容量 患者，特别是那些高危和获得护理机会较差的患者，基于ED的糖尿病筛查可以 帮助识别未诊断的病例，并提供将新诊断的患者与 适当的门诊护理。在任何一年，近五分之一的美国人去看急诊室，超过50%的急诊室 患者接受某种类型的血液测试。纽约大学朗格尼健康中心最近发起了一项全系统的倡议 用糖化血红蛋白检测筛查已接受血检的ED患者。我们的初步数据表明 这种筛查方法可以帮助识别患有先前未诊断的糖尿病的ED患者，特别是在 少数群体和没有正规初级保健提供者的人。最关键的实际考虑因素是 这一举措带来的问题是如何改善门诊护理的后续工作。只有23%的新用户 确诊的患者在我们的医疗保健系统内进行了门诊随访。虽然这些患者可能 这一统计数字与急诊科就诊后的低随访率一致。因此，这 该提案旨在解决以下问题：(1)哪些患者最不可能在新的 糖尿病的诊断；(2)这些患者没有作为门诊患者进行随访的主要原因是什么？ (3)有针对性的干预措施是否有助于弥合这些保健方面的差距。因此，本研究将向临床发展。 算法使用电子健康记录中的数据来识别哪些患者最不可能对 患者在新诊断为糖尿病后的护理。它还将进行详细的定性访谈 在这些新诊断的ED患者中，没有得到随访以全面了解 他们的关爱障碍。我们还将进行远程医疗与ED患者联系的随机对照试验 确诊为新诊断的糖尿病患者到适当的门诊治疗。这项研究将有助于改进 通过测试可扩展模型将EDS转换为临床环境，从而有效地监控糖尿病 对每年到美国急诊室就诊的数百万高危患者进行筛查和转介，从而 减少诊断差异、糖尿病并发症的频率和糖尿病相关的早期死亡。

PROJECT SUMMARY Of the millions of Americans who visit an emergency department (ED) each year, there are substantially higher rates of ED use among racial and ethnic minorities and patients with significant socioeconomic barriers. However, EDs rarely provide any sort of preventive care, and the care they provide is often not well coordinated with critically important outpatient care. The consequences are higher rates of undiagnosed diseases like diabetes among ED patients, which then go untreated, exacerbating health disparities, poor glycemic control, diabetic complications, and early diabetes-related death. Given the high volume of ED patients, especially those who are high-risk and have poor access to care, ED-based diabetes screening can help identify undiagnosed cases and presents an important opportunity to link newly diagnosed patients to appropriate outpatient care. Nearly 1 in 5 Americans visit an ED in any given year and more than 50% of ED patients receive some type of blood test. NYU Langone Health has recently launched a system-wide initiative to screen ED patients already receiving blood work using HbA1c tests. Our preliminary data demonstrate that this screening approach can help identify ED patients with previously undiagnosed diabetes, especially among minorities and those without a regular primary care provider. The most critical practical consideration that has emerged from this initiative is how to improve follow-up with outpatient care. Only 23% of these newly diagnosed patients had a follow-up outpatient visit within our healthcare system. While these patients may have had visits elsewhere, this statistic is consistent the low rates of follow-up after ED visits. Therefore, this proposal seeks to address the following questions: (1) which patients are least likely to follow-up after a new diagnosis of diabetes, (2) what are the primary reasons why these patients do not follow-up as outpatients, and (3) whether targeted interventions can help bridge these gaps in care. Therefore, this study will develop clinical algorithms using data from electronic health records to identify which patients are least likely to follow-up for patient care after being newly diagnosed with diabetes. It will also perform detailed qualitative interviews among these newly diagnosed ED patients who fail to follow-up to obtain a comprehensive understanding of their barriers to care. We will also perform a randomized controlled trial of telemedicine to link ED patients identified as having newly diagnosed diabetes to appropriate outpatient care. This study will help improve diabetes surveillance by testing a scalable model to transform EDs into a clinical setting that can effectively screen and refer the millions of high-risk patients that visit EDs in the United States each year, thereby reducing disparities in diagnoses, the frequency of diabetic complications, and early diabetes-related death.