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

项目摘要 严重精神疾病（SMI）患者患2型糖尿病的风险是普通人的两倍。 人口中的高死亡率，导致心血管疾病和过早死亡率较高。共同使用 抗精神病药物由于普遍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循证心脏代谢疾病预防护理。 未充分使用的策略包括：开替代的、不太致胖的精神药物;生活方式 改变支持;额外的降低风险的药物;和戒烟治疗。我们的初步 患者和临床医生的定性数据确定了将预防护理与个人健康相匹配的工具的需求。 风险水平和偏好，以及适合于基于人口的护理战略的工具。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策，促进循证护理。 通过这个指导K23职业发展奖，Esti Iturralde博士将建立在她的背景， 临床心理学家和行为糖尿病研究者。通过有计划的指导、课程和职业生涯 通过发展活动，Iturralde博士将获得对精神药理学的深刻理解， 心脏代谢健康、高级预测分析和实施科学，包括 参与干预设计和实用的临床试验。作为一个研究者在德皇 永久北方加州（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/族裔群体的超过50，000名成年人）和利益相关者 卫生系统内的见解（患者，临床医生和卫生系统决策者），包括KPNC和2 其他人属于NIMH资助的心理健康研究网络（健康伙伴研究所和亨利 福特卫生系统）。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，旨在增加有针对性的、循证的糖尿病和心血管疾病 为45岁以下开始服用抗精神病药物的成年人提供疾病预防护理。具体研究 目标是：（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）让利益相关者参与CDS工具信息的设计， 实施途径;以及通过一项实用的临床试验， 现有的KPNC远程保健为基础的人口管理方案为这一人群服务。未来R01 应用程序将建立在该项目的结果，以进一步完善和测试CDS工具在多个健康 系统.相关的研究和培训目标将直接为Iturralde博士作为嵌入式企业的成功做好准备。 卫生系统研究员，并准备她领导一个项目线的研究开发和实施 数据驱动的、可行的、可扩展的干预措施，改善SMI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.