Using Real-world Data to Assess the Burden of Diabetes in Children and Adolescents in Florida

摘要 强有力的证据表明，1型和2型糖尿病（T1 DM & 自2000年以来，美国（US）和全球儿童和青少年中的T2 DM。重要的种族- 在糖尿病发病率和获得护理方面也有种族和地理差异， 代谢控制在这个脆弱的群体。这些令人震惊的观察需要及时监测 儿童和青少年糖尿病发病的系统，以便量身定制的公共卫生计划， 发展和卫生保健资源可以有效地分配，以满足这些弱势群体的需要， 组及时。然而，对这一特定人群的糖尿病监测研究有限， 美方目前儿童糖尿病患病率和发病率估计的主要来源， 美国疾病预防控制中心的青少年糖尿病研究来自青少年糖尿病研究，该研究依赖于 来自十个州的注册临床中心的活跃病例报告系统。这项研究是 然而，重要的是不包括东南地区的大多数人口， 发现糖尿病患病率在该国成年人口中是最高的（即，糖尿病 皮带”）。我们对该地区儿童和青少年糖尿病的患病率和发病率知之甚少， 包括佛罗里达在内的其他州也是全国最高的。 在这项拟议的研究中，我们将在佛罗里达建立一个监测系统，以监测 儿童和青少年的糖尿病，以准确，具有成本效益和及时的方式。作为第三大 佛罗里达是美国人口众多的州，种族和地理差异很大， 作为国家糖尿病监测系统的重要组成部分，并提供重要的研究数据。 美国东南部地区儿童和青少年的糖尿病流行病学， 是全国最普遍的我们将利用我们独特的真实世界数据（RWD）源， OneFlorida网络，一个大型的全州范围的RWD存储库，包含链接的EHR，索赔，重要统计数据， 和出生记录数据，覆盖所有67个佛罗里达县超过60%的佛罗里达人， 糖尿病监测系统特别是，我们将联合收割机结合结构化和非结构化数据（例如， 医生的笔记），以开发新的数据驱动的可计算表型（CP）算法 通过现代机器学习方法，使我们对T1 DM患病率和发病率的估计 和T2 DM将比先前的基于EHR的系统更准确。这项研究还将产生重要的数据 研究健康的社会和行为决定因素以及许多其他潜在的影响因素， 导致糖尿病的种族-种族和地理差异，在两个个体（例如，个人健康 行为）和上下文级别（例如，地区一级的代谢控制计划）。

ABSTRACT Strong evidence suggests an increasing trend of diabetes onset for both type 1 and type 2 diabetes (T1DM & T2DM) among children and adolescent in the United State (US) and globally since 2000. Significant racial- ethnic and geographic disparities have also been documented in diabetes incidence and in access to care and metabolic control in this vulnerable population. These alarming observations call for a timely surveillance system for the onset of diabetes among children and adolescents, so that tailored public health programs can be developed and health care resources can be efficiently allocated to address the needs of these vulnerable groups in a timely manner. However, diabetes surveillance studies on this particular population are limited in the US. The primary source for current prevalence and incidence estimates of diabetes among children and adolescents in the US for the CDC is from the SEARCH for Diabetes in Youth (SEARCH) study, which relies on an active case reporting system from enrolled clinical centers over ten states. The SEARCH study is important, however, does not include the majority of the population located at the south-east region, where diabetes prevalence was found to be the highest in the country among the adult population (i.e., the “diabetes belt”). Less is known if the prevalence and incidence of diabetes among children and adolescents in this area, including Florida, are also the highest in the country. In this proposed study, we will build a surveillance system in Florida to monitor the prevalence and incidence of diabetes among children and adolescents in an accurate, cost-effective, and timely fashion. As the 3rd-most populous state in the United States with a high level of racial-ethnical and geographic diversities, Florida will serve as an essential piece for the national diabetes surveillance system and provide important data to study the diabetes epidemiology among children and adolescents in the south-east region of the US where diabetes was found the most prevalent in the country. We will leverage our unique real-world data (RWD) source, the OneFlorida network, a large state-wide repository of RWD that contains linked EHRs, claims, vital statistics, and birth records data, covering more than 60% of Floridians across all 67 Florida counties to build this diabetes surveillance system. In particular, we will combine the structured and unstructured data (e.g., physician’s notes) from patients EHRs to develop novel data-driven computable phenotyping (CP) algorithms through modern machine learning methods, so that our estimations on the prevalence and incidence of T1DM and T2DM will be more accurate than prior EHRs-based systems. This study will also generate important data to study the social and behavioral determinants of health among many other potential contributing factors that results in ethnic-racial and geographic disparities of the diabetes, at both individual (e.g., individual health behaviors) and contextual levels (e.g., area-level access to metabolic control programs).