Addressing Social Determinants in Diabetes Care: the REDD-CAT health-related social needs screening tool

项目总结 超过2700万美国人患有2型糖尿病，占770多万 入院人数和每年2450亿美元的医疗费用。住院的2型糖尿病患者在 增加再次入院的风险；2010年，20.3%的糖尿病患者有并发症再次入院 在30天内，使糖尿病成为再次住院的首要条件之一。在许多情况下，社会 健康的决定因素--如住房和食品不稳定、福利被拒绝和缺乏收入--是 负责可预防的住院治疗，因为它们削弱了患者自我管理糖尿病的能力 并防止并发症。通常，这些未得到满足的社会需求是在临床过程中非正式地确定的 关心。然而，没有简化的流程来全面确定、确定优先顺序和解决最多问题 我们最脆弱患者的重要健康相关社会需求。我们之前的研究增加了我们的 了解与再入院风险和不良结局相关的多种社会决定因素。它有 强调制定有效评估和确定社会决定因素和优先事项的方法的重要性 建立重新入院风险最高的人的个人资料。我们建议开发一种测量方法 用于糖尿病的重新设计的出院-计算机适应测试(REDD-CAT)系统，以有效捕获 并为糖尿病患者创建与健康相关的社会需求的个性化配置文件，以减少可避免的 住院和急诊科就诊。我们的目标是：1)开发和验证REDD-CAT；2) 为了利用新开发的REDD-CAT措施，来自PROIS的现有措施，医疗记录数据， 和追溯索赔数据，以生成个性化风险评估简档；以及3)进行试点 评估在临床上实施REDD-CAT的可接受性的可行性试验。取得的成就 这三个目标将为实施REDD-CAT的前瞻性随机试验奠定基础。 医院环境，以评估其对30天再入院的影响。作为我们建议的评估工具的名称 意味着，我们研究的长期目标是为重新设计的排放创造一个过程 并将REDD-CAT作为主要数据来源嵌入这一进程。最终，我们预计 我们用来研究和开发REDD-CAT的方法将在许多领域得到广泛应用 不同的环境和慢性病。

PROJECT SUMMARY Over 27 million Americans have Type 2 Diabetes Mellitus (T2DM), accounting for more than 7.7 million hospital admissions and $245 billion in healthcare costs each year. Hospitalized T2DM patients are at increased risk of readmission; in 2010, 20.3% of patients admitted for DM with complications were readmitted within 30 days, making diabetes one of the top conditions for rehospitalizations. In many instances, the social determinants of health—such as housing and food instability, benefits denials, and lack of income—are responsible for preventable hospitalizations, as they undermine the patient’s ability to self-manage diabetes and prevent complications. Often these unmet social needs are informally identified in the course of clinical care. However, there is no streamlined process to comprehensively identify, prioritize, and address the most important health-related social needs of our most vulnerable patients. Our previous research has increased our understanding of the multitude of social determinants related to readmission risk and poor outcomes. It has underscored the importance of developing methods to efficiently assess and prioritize social determinants and to develop profiles of the individuals at the highest risk of readmission. We propose to develop a measurement system, Re-Engineered Discharge for Diabetes-Computer Adaptive Testing (REDD-CAT) to efficiently capture and create a personalized profile of health-related social needs for patients with diabetes to reduce avoidable hospitalization and emergency department visits. Our aims are: 1) to develop and validate the REDD-CAT; 2) to utilize the newly developed REDD-CAT measures, existing measures from PROMIS, medical record data, and retrospective claims data to generate personalized risk assessment profiles; and 3) to conduct a pilot feasibility trial to assess the acceptability of implementing the REDD-CAT in a clinical context. Achievement of these three aims will set the stage for a prospective, randomized trial of the REDD-CAT implementation in a hospital setting to assess its impact on 30-day readmissions. As the name of our proposed assessment tool implies, the longer-term goal of our research is to create a process for the Re-Engineered Discharge for Diabetes and to embed the REDD-CAT in this process as the primary data source. Ultimately, we anticipate that the methods we use to research and develop the REDD-CAT will find wide application across a number of different settings and chronic diseases.