Epidemiology and clinical outcomes of diabetic macular edema

在数百万退伍军人中，约有25%(估计。892万人)登记参加退伍军人健康护理 给药(VHA)有糖尿病，而糖尿病黄斑水肿(DME)是视力的主要原因 在全球成年糖尿病人口中的损失。虽然糖尿病视网膜病变已经得到了很好的研究， 人们对二甲醚的负担知之甚少。事实上，只有两项全国性的流行率研究，没有 对2型糖尿病患者中二甲基醚的发病率进行了全国性的研究。同样多的 糖尿病视网膜病变的危险因素已被定性，但尚未有大型研究确定DME的预测因素。 除了Medicare索赔数据库，VHA National Patient Care数据库(NPCD)还包含 病人护理的几个方面的标准化管理数据，包括诊断、程序、 药物、实验室测试结果、生命体征、临床记录和死亡率。因为退伍军人事务部使用了电视 筛查作为所有糖尿病患者的常规临床护理，这些结果包括在NPCD， NPCD是研究DME流行病学和危险因素的理想来源。 这项研究建议确定糖尿病黄斑水肿的负担，建立危险因素，并 检查之前提取的198万名退伍军人的治疗结果 自2004年以来至少进行一次糖尿病视网膜病变筛查。目前，无价的眼科数据被编码为 计算机化患者记录系统(CPRS)中的非结构化临床遭遇记录，且未经验证 存在自动提取方法来捕获这些数据元素。一种自动提取方法，使用 将创建并验证自然语言处理，以解锁关键的眼科变量。这些文本 提取方法将适用于从患者的笔记中提取眼科数据 DME还有任何眼科临床笔记。这将使未来眼科的大规模研究成为可能。 使用NPCD，并立即对整个研究界产生价值。 候选人Aaron Lee博士，MSCI医学博士，是一名接受过视网膜专科培训的眼科医生 具有计算机科学和流行病学专业背景的外科专业。他的职业目标是成为一名 独立临床科学家利用大规模电子病历研究糖尿病眼病 提取的数据。虽然他拥有基本技能，但他寻求获得高级统计和 自然语言处理，以解锁在非结构化临床遭遇记录中捕获的数据。他有 在主要导师爱德华·博伊科博士的带领下组建了一支出色的导师团队，医学博士，公共卫生硕士。这 导师团队包括临床流行病学、健康信息学、眼科和 自然语言处理。这个K23课程将为李博士提供有组织的课程、指导和应用 学习需要获得新的研究技能。他将利用关键的当地资源来执行拟议的 华盛顿大学和退伍军人事务部西雅图流行病学研究和信息中心的研究。

Approximately 25% of the millions of veterans (est. 8.92 million FY 2013) enrolled for care in Veterans Health Administration (VHA) have diabetes mellitus, and diabetic macular edema (DME) is the leading cause of vision loss in the adult diabetic population world-wide. Although diabetic retinopathy has been well-studied, comparatively little is known about the burden of DME. In fact, only two national prevalence studies and no national study on the incidence of DME in persons with type 2 diabetes have been conducted. Similarly many risk factors have been characterized for DR, but no large studies have established predictors for DME. Beyond the Medicare claims database, the VHA National Patient Care Database (NPCD) contains standardized administrative data for several aspects of patient care including diagnoses, procedures, medications, lab test results, vital signs, clinical text notes, and mortality. Because the VA uses teleretinal screening as routine clinical care for all patients with diabetes with these results included in the NPCD, the NPCD is an ideal source for studying the epidemiology of and risk factors for DME. This study proposes to determine the burden of diabetic macular edema, establish risk factors, and examine treatment outcomes in a previously extracted dataset on 1.98 million veterans who have undergone diabetic retinopathy screening at least once since 2004. Currently invaluable ophthalmic data are encoded in unstructured clinical encounter notes in the Computerized Patient Record System (CPRS), and no validated automated extraction method exists to capture these data elements. An automated extraction method using natural language processing will be created and validated to unlock key ophthalmic variables. These text extraction methods will be applicable to extracting ophthalmology data from not only notes of patients with DME but also any ophthalmology clinical note. This will enable future large scale studies in ophthalmology using NPCD and be immediately valuable to the research community at large. The candidate, Dr. Aaron Lee, MD MSCI, is an ophthalmologist with subspecialty training in retina surgery with a strong background in computer science and epidemiology. His career goal is to become an independent clinician scientist studying diabetic eye disease with large-scale electronic medical record extracted data. While he possesses the foundational skills, he seeks to gain training in advanced statistics and natural language processing to unlock the data captured in unstructured clinical encounter notes. He has assembled an outstanding mentorship team under the primary mentor, Dr. Edward Boyko, MD MPH. This mentorship team includes renowned experts in clinical epidemiology, health informatics, ophthalmology, and natural language processing. This K23 will provide Dr. Lee the structured coursework, mentorship, and applied learning needed to acquire new research skills. He will leverage key local resources to carry out the proposed research at the University of Washington and the VA Seattle Epidemiologic Research and Information Center.