Optimizing Care to Prevent Diabetes and Promote Cardiovascular Health Among Younger Adults with Severe Mental Illness

项目总结 患有严重精神疾病(SMI)的人患2型糖尿病的风险是普通患者的两倍 人口，导致心血管疾病和过早死亡的比率较高。的常见用法 抗精神病药物由于普遍存在的代谢副作用而导致这些健康风险。许多 患有SMI的年轻人没有接受有针对性的、基于证据的心脏代谢性疾病预防护理。 未得到充分利用的策略包括：开出替代的、致肥胖较少的精神药物；生活方式 改变支持；额外的降低风险的药物；以及戒烟疗法。我们的预赛 患者和临床医生的定性数据确定了对工具的需求，以便将预防护理与个人 风险水平和偏好，以及适合以人口为基础的护理战略的工具。临床决策支持 (CDS)工具是使用患者数据、预测性分析和临床指南的计算机算法 通过帮助患者和临床医生做出复杂的治疗决定，促进循证护理。 通过这个有指导的K23职业发展奖，Esti Iturralde博士将在她作为 临床心理学家和行为糖尿病研究人员。通过有计划的指导、课程作业和职业生涯 发展活动，伊图拉尔德博士将对精神药理学和 心脏代谢健康、高级预测分析和实施科学，包括 利益相关者参与的干预设计和务实的临床试验。作为《帝王报》的研究员 常住北加州(KPNC)研究部(DOR)，她将利用强大的纵向 电子健康记录(EHR)数据(来自不同种族/民族的50,000名成年人)和利益相关者 对包括KPNC和2在内的卫生系统的洞察(患者、临床医生和卫生系统决策者) 其他属于NIMH资助的精神健康研究网络(HealthPartners Institute和Henry 福特健康系统)。拟议的研究将支持培训目标，同时有助于 开发一种新的CDS工具，寻求增加靶向、循证的糖尿病和心血管疾病 为开始服用抗精神病药物的45岁以下成年人提供疾病预防护理。具体研究 目的是：(1)通过开发和验证糖尿病风险预测，为CDS工具的预测分析提供信息 目标人群的模型；(2)让利益攸关方参与CDS工具的设计和 实施路径；通过在以下方面进行的实用临床试验传递现场测试CDS工具消息 一个现有的基于KPNC远程健康的人口管理计划，服务于这些人口。未来的R01 应用程序将以此项目的结果为基础，在多个运行状况下进一步改进和测试CDS工具 系统。相关的研究和培训目标将直接为伊图拉尔德博士作为一名嵌入式医生的成功做好准备 卫生系统研究员，并使她做好准备，领导制定和实施一系列方案研究 数据驱动的、可行的、可扩展的干预措施，改善重度心肌梗死患者的心脏代谢健康。

PROJECT SUMMARY People with severe mental illness (SMI) face double the risk for type 2 diabetes compared to the general population, contributing to higher rates of cardiovascular disease and premature death. Common use of antipsychotic medications contributes to these health risks due to prevalent metabolic side effects. Many younger adults with SMI do not receive targeted, evidence-based cardiometabolic disease prevention care. Underused strategies include: prescribing alternative, less obesogenic psychotropic medications; lifestyle change supports; additional risk-reducing medications; and smoking cessation therapies. Our preliminary qualitative data with patients and clinicians identified a need for tools to match prevention care to individuals’ risk level and preferences, and tools suited to population-based care strategies. Clinical Decision Support (CDS) tools are computer algorithms that use patients’ data, predictive analytics, and clinical guidelines to promote evidence-based care by helping patients and clinicians navigate complex treatment decisions. Through this mentored K23 career development award, Esti Iturralde, PhD will build upon her background as a clinical psychologist and behavioral diabetes researcher. Through planned mentoring, coursework, and career development activities, Dr. Iturralde will gain a strong understanding of psychopharmacology and cardiometabolic health, advanced predictive analytics, and implementation science, including methods for stakeholder-engaged intervention design and pragmatic clinical trials. As a researcher in the Kaiser Permanente Northern California (KPNC) Division of Research (DOR), she will leverage robust, longitudinal electronic health record (EHR) data (> 50,000 adults from diverse racial/ethnic groups) and stakeholder insights (patients, clinicians, and health system decision-makers) within health systems including KPNC and 2 others belonging to the NIMH-funded Mental Health Research Network (HealthPartners Institute and Henry Ford Health System). The proposed research will support the training goals while contributing to the development of a novel CDS tool seeking to increase targeted, evidence-based diabetes and cardiovascular disease prevention care for adults under age 45 who are starting antipsychotic medications. Specific research aims are to: (1) inform predictive analytics of the CDS tool by developing and validating diabetes risk prediction models for the target population; (2) engage stakeholders in the design of CDS tool messaging and implementation pathways; and field-test CDS tool messaging through a pragmatic clinical trial conducted within an existing KPNC telehealth-based population management program serving this population. A future R01 application will build on the results from this project to further refine and test the CDS tool within multiple health systems. The linked research and training aims will directly prepare Dr. Iturralde for success as an embedded health system researcher and prepare her to lead a programmatic line of studies developing and implementing data-driven, feasible, scalable interventions improving the cardiometabolic health of people with SMI.