Methods Core

方法核心

• 批准号: 10021733
• 负责人: GREGORY E. SIMON
• 金额: $ 21万
• 依托单位: KAISER FOUNDATION RESEARCH INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-23 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10021733
• 关键词: Address; Adverse effects; Antipsychotic Agents; Area; Chronic; Clinical; Clinical Research; Code; Consultations; Data; Development; Diagnosis; Evaluation; Funding; Goals; Grant; Health Services Research; Health system; Individual; Informatics; Integrated Health Care Systems; Interest Group; Laboratories; Learning; Machine Learning; Mental Depression; Mental Health; Methods; National Institute of Mental Health; Network Infrastructure; Network-based; Observational epidemiology; Outcome Assessment; Patient Outcomes Assessments; Patients; Pattern; Perinatal Exposure; Population; Practice based research; Predictive Analytics; Primary Health Care; Privacy; Qualitative Research; Request for Applications; Research; Research Design; Research Infrastructure; Research Methodology; Research Personnel; Research Project Grants; Resources; Risk; Speed; Study models; Suicide prevention; Treatment Failure; Trust; Work; Youth; analytical method; analytical tool; data infrastructure; data quality; data resource; design; first episode psychosis; health care delivery; health data; implementation science; improved; individualized medicine; large scale data; learning community; member; method development; next generation; patient population; perinatal mental health; practice-based research network; pragmatic trial; prenatal exposure; programs; public repository; research and development; risk prediction model; social health determinants; suicidal risk; tool development; treatment effect; treatment strategy

We propose to expand the existing Mental Health Research Network (MHRN) to include 14 research centers embedded in large health systems serving a combined population of over 25 million patients in 16 states. MHRN infrastructure will be enhanced to support a next-generation research network, including: • Expansion of data resources regarding patient-reported outcomes from real-world practice • Development of new data resources in high-priority areas (e.g. perinatal exposures) • A Scientific Analysis interest group to increase the rigor of analytic methods across MHRN projects • Methods development focused on evaluation of adaptive treatment strategies for people with more severe mental health conditions and on predictive analytic tools designed to address stakeholder priorities This overall application requests support for an Administrative Core, a Methods core, two Signature research projects and two Pilot research projects. The Methods Core will include an Informatics Unit, led by Drs. Gregory Simon and Christine Stewart, and a Scientific Analysis Unit, led by Drs. Susan Shortreed and Patrick Heagerty. The Informatics Unit will continue highly successful work over the past 8 years, supporting routine data quality assessment and descriptive analyses of diagnosis and treatment patterns across all participating health systems. New work will include development of tools and resources to assess and minimize privacy risks when sharing sensitive health data for research and development of specific new data areas (perinatal mental health and prenatal exposures, expanded list of patient-reported outcomes, and assessments of social determinants of health). The Informatics Unit will provide consultation to all MHRN core and affiliated projects and share all resources with other researchers and health systems via MHRN's public repository of specifications, code lists, and analytic code. The Scientific Analysis Unit will support to all MHRN core and affiliated projects via project-specific consultation and development of a learning community of analysts and biostatisticians across MHRN research centers. This Unit will also focus on development and dissemination of analytic methods in two areas directly relevant to MHRN research. Work on evaluating adaptive treatment strategies will build on Dr. Shortreed's recently funded methods grant to evaluate and disseminate methods for using health system data to tailor treatments for individuals with more chronic or severe mental health conditions, focusing on assessing treatment effects when treatments are adjusted or switched according to previous treatment failures or adverse effects. Work on stakeholder-driven predictive analytics will build on MHRN's development of accurate suicide risk prediction models, focusing on matching specific study designs and model development methods with stakeholder priorities and implementation constraints.

我们建议扩大现有的心理健康研究网络（MHRN），使其包括14个研究中心