MODELING TREATMENT USE & EFFECTIVENESS IN MENTAL ILLNESS

模拟治疗使用

• 批准号: 6499366
• 负责人: SHARON-LISE Teresa NORMAND
• 金额: $ 41.01万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-02-01 至 2004-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6499366
• 关键词: human data; major depression; mathematical model; mental disorder chemotherapy; model design /development; psychotherapy; schizophrenia; therapy compliance

DESCRIPTION (Applicant's abstract): This application seeks support for a team of statisticians, economists, clinicians, and mental health services researchers to collaborate on the development and application of discrete choice models for understanding treatment use and for causal inferences in experimental and naturalistic studies of mental illness. By studying how patients are matched with treatments in extant systems, researchers will gain greater insight into the determinants of quality of care. The Specific Aims will involve the 1) extension of likelihood-based methods to estimate treatment effectiveness at the levels actually received using experimental data from two influential clinical trials (Schulberg, Block, Madonia et al., Acrh Gen Psychiatry 1996;53:913-9 & Rosenheck, Neale, Arch Gen Psychiatry 1998;55:459-66) and to compare these estimates with those based on conventional approaches, such as intention-to-treat, adequate, and completer principles, 2) development of new models of discrete choice to explain variation in treatment use based on patient, provider, and insurance characteristics for privately insured and Medicaid beneficiaries, and 3) application of these discrete choice models to explain variation in adherence with treatment recommendations and in treatment effectiveness for depression and for schizophrenia across a diverse array of practice settings. An Advisory Board comprised of leaders in statistics, economics, and psychiatry will convene annually to validate methods and ensure integration of techniques into mental health services research. The methodological advances from this research will enable mental health researchers and policy makers to better characterize usual care and to expand the inferences drawn from clinical trials.

描述（申请人摘要）：此申请寻求团队支持 统计学家、经济学家、临床医生和心理健康服务机构 研究人员合作开发和应用离散 用于理解治疗使用和因果推断的选择模型 精神疾病的实验和自然主义研究。通过研究 患者与现有系统中的治疗方法相匹配，研究人员将获得 更深入地了解护理质量的决定因素。具体目标 将涉及1）扩展基于可能性的方法来估计治疗 实际收到的水平的有效性使用两个实验数据 有影响力的临床试验（Schulberg，Block，Madonia等，Acrh Gen 精神病学1996;53：913-9 & Rosenheck，Neale，Arch Gen Psychiatry 1998;55：459-66），并将这些估计值与基于常规方法的估计值进行比较。 方法，如意向治疗、充分和完成原则，2） 开发新的离散选择模型，以解释治疗差异 基于患者、提供者和保险特征的使用， 被保险人和医疗补助受益人，以及3）这些离散选择的应用 模型来解释治疗建议依从性的变化， 抑郁症和精神分裂症的治疗效果 一系列的实践设置。一个由领导人组成的咨询委员会， 统计学、经济学和精神病学将每年召开一次会议， 并确保将技术融入精神卫生服务研究。的 这项研究的方法学进步将使心理健康 研究人员和政策制定者更好地描述常规护理， 从临床试验中得出的结论