Laboratory for Early Psychosis Research (LEAP)

早期精神病研究实验室 (LEAP)

• 批准号: 10376216
• 负责人: MIGUEL HERNAN
• 金额: $ 163.46万
• 依托单位: MCLEAN HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-15 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10376216
• 关键词: Accounting; Address; Administrator; Adverse effects; Advocate; Attention; Binding; Caring; Clinic; Clinical; Clinical Trials; Collaborations; Community Outreach; Comparative Effectiveness Research; Complement; Coordinated Specialty Care; Country; Data; Data Collection; Data Science; Data Set; Databases; Discipline; Disease; Early Intervention; Economics; Education and Outreach; Epidemiology; Event; Faculty; Family; Foundations; Funding; Future; Goals; Growth; Health Policy; Health system; Hospitalization; Information Systems; Insurance; Knowledge; Laboratories; Learning; Machine Learning; Massachusetts; Measures; Mental Health; Methods; Modernization; Morbidity - disease rate; National Institute of Mental Health; North America; Operations Research; Outcome; Outcome Measure; Patient Care; Patient Outcomes Assessments; Patient-Focused Outcomes; Patients; Pattern; Policies; Policy Maker; Population; Process; Protocols documentation; Psychoses; Psychotic Disorders; Research; Research Methodology; Research Personnel; Resource Sharing; Resources; Schizoaffective Disorders; Schizophrenia; Science; Scientist; Source; Standardization; Structure; Students; Subgroup; System; Time; Work; base; care outcomes; clinical heterogeneity; data harmonization; data quality; design; early psychosis; faculty community; first episode psychosis; health care delivery; improved; individual patient; interdisciplinary collaboration; knowledge base; machine learning prediction; mortality; statistics; symposium; treatment effect; web site

1. Abstract We propose to create a NIMH P50 ALACRITY Center that develops the collaborations, data systems, and methods necessary to form a state-wide Laboratory for Early Psychosis Research, aka the LEAP Center. While recent trial evidence suggests great promise for coordinated specialty care (CSC) for patients with first episode psychosis (FEP), there remain several gaps in the knowledge base for the care of psychosis in general. Now is an ideal time to address these gaps because of recent policy changes enhancing FEP care financing, practice changes in the field, and methods developed outside of mental health. To create this Center, we will start with interdisciplinary collaborations between CSC clinics in Massachusetts, policy makers/regulators, and stakeholders, and include FEP experts from across the country plus scientific experts from outside of mental health, e.g., in data science, machine learning, epidemiology, and health policy. We also will leverage recent Massachusetts efforts to mandate, standardized, and support data collection on FEP care structures, delivery, and outcomes from all FEP clinics within the state. We also will apply and develop modern methods for clinical prediction and comparative effectiveness research (CER), e.g., machine learning and g-methods, for FEP research. Accordingly, we have three overall Center aims: 1) Collaborations; 2) Data systems; and 3) Prediction and CER methods. The Center will start with three foundational and complementary projects: 1) Using the state All Payer Claims Database (APCD), Project 1 will apply a population-level approach to examine which patients receive care in FEP clinics offering CSC versus elsewhere, as the number of clinics increases, then estimate the treatment effect on unfavorable clinical event rates such as hospitalizations; 2) Project 2 will review the data collected by the state from all of the FEP clinics, assess and improve data collection quality, validate measures, and integrate perspectives; and 3) Project 3 will define clusters of patients using longitudinal outcome data (i.e., begin to unpack the amount of clinical heterogeneity), predict the cluster type for individual patients, and examine the impact of CSC treatment accounting for this clinical heterogeneity. The Administrative Core and Methods Core (Prediction and CER) bind these projects together. The Center will include a group of Scientific Advisors from across North America, Center Faculty from diverse scientific disciplines, including those that historically have had little exposure in mental health research, and Stakeholders, including policy makers, organizational decision makers, and patient and family advocates. All three groups will be deeply involved in the Center from design to dissemination. The overall goal is to create a state-wide learning health system for early psychosis. This effort to create the protocols and apply the methods necessary to convert large amounts of data into useful clinical and policy knowledge will inform other national efforts, e.g., NIMH’s EPINET.

1.摘要 我们建议创建一个NIMH P50 ALACRITY中心，负责开发协作、数据系统和 必要的方法，形成一个全州范围的实验室早期精神病研究，又名LEAP中心。 虽然最近的试验证据表明，对首次出现的患者进行协调专科护理（CSC）的前景很好， 精神病发作（FEP），在精神病护理的知识基础上仍然存在一些差距， 将军现在是解决这些差距的理想时机，因为最近的政策变化加强了FEP护理 融资、该领域的实践变化以及在心理健康之外开发的方法。创建这个 中心，我们将开始与CSC诊所之间的跨学科合作，在马萨诸塞州，政策 制造商/监管机构和利益相关者，包括来自全国各地的FEP专家和科学专家 从精神健康之外，例如，数据科学、机器学习、流行病学和卫生政策。我们 我还将利用最近马萨诸塞州的努力，授权、标准化和支持关于FEP的数据收集 护理结构，交付，以及该州所有FEP诊所的结果。我们还将应用和开发 临床预测和比较有效性研究（CER）的现代方法，例如，机器学习 和g方法，用于FEP研究。因此，我们有三个总体中心目标：1）合作; 2）数据 系统; 3）预测和CER方法。该中心将从三个基础和互补的 项目：1）使用国家所有付款人索赔数据库（APCD），项目1将适用人口水平 检查哪些患者在提供CSC的FEP诊所接受护理，而不是在其他地方， 诊所的增加，然后估计对不利临床事件发生率的治疗效果，例如 2）项目2将审查国家从所有FEP诊所收集的数据，评估和 提高数据收集质量，验证措施，并整合观点; 3）项目3将定义 使用纵向结果数据的患者群（即，开始解包临床异质性的量）， 预测个体患者的聚类类型，并检查CSC治疗对此的影响 临床异质性管理核心和方法核心（预测和CER）将这些项目联系在一起 一起该中心将包括一组来自北美各地的科学顾问，来自 不同的科学学科，包括那些历史上很少接触心理健康研究的学科， 和利益相关者，包括政策制定者、组织决策者以及患者和家庭倡导者。 这三个小组将深入参与中心从设计到传播的工作。总体目标是创造 全州范围内的早期精神病学习健康系统创建协议并应用 将大量数据转化为有用的临床和政策知识所需的方法将告知其他人， 国家努力，例如，NIMH的EPINET。