Marketplace Readiness of a Novel Transdiagnostic Assessment for Clinical Research and Practice

用于临床研究和实践的新型跨诊断评估的市场准备情况

• 批准号: 10323067
• 负责人: Tara Thiagarajan
• 金额: $ 32.17万
• 依托单位: SAPIEN HEALTH LLC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-16 至 2022-07-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10323067
• 关键词: Address; Adoption; Architecture; Area; Assessment tool; Attention; Categories; Clinical; Clinical Assessment Tool; Clinical Research; Clinical assessments; Code; Communities; Consumption; Critiques; Data; Development; Devices; Diagnosis; Diagnostic; Dimensions; Disease; Elements; Ensure; Environment; Frequencies; Future; Grouping; Health; Health Insurance Portability and Accountability Act; Heterogeneity; Individual; Intelligence; Label; Learning; Life; Life Experience; Maps; Mental Health; Mental disorders; Outcome; Outcomes Research; Output; Patient Recruitments; Patients; Phase; Phenotype; Population; Prognosis; Psyche structure; Pythons; Readiness; Regimen; Reporting; Research; Research Domain Criteria; Risk; Sampling; Screening procedure; Small Business Innovation Research Grant; Subcategory; Symptoms; System; Testing; Time; Treatment Protocols; Validation; Variant; base; clinical application; clinical development; clinical phenotype; clinical practice; comorbidity; design; experience; file format; health assessment; individual patient; insight; instrument; mental development; novel; personalized diagnostics; personalized screening; screening; systems research; tool; treatment choice; treatment research; usability; web-enabled

ABSTRACT In this SBIR Phase 1 proposal, we aim to develop and automate the workflow for a comprehensive transdiagnostic mental health assessment tool for increased precision in the screening of mental health. The majority of instruments presently in use have been designed based on DSM criteria, which has been critiqued for being theoretically defined and ignoring the heterogeneity of symptoms across patients. Furthermore, individual tools are incomplete and heterogeneous in their assessment of symptoms for the same disorder. Thus, individuals are placed into pre-defined categories that do not reflect their overall symptom experience and life factors, and diagnosis can vary based on the choice of tool. This makes it difficult and time consuming to understand individual patients to determine treatment trajectories, effectively recruit patients into research trials, and understand outcomes based on complete symptom phenotypes. In order to address these challenges, a novel assessment tool, the cMHQ, has been developed by our partner non-profit research organization, Sapien Labs, and provides a comprehensive patient symptom profile that maps across 10 DSM-based mental health disorders, as well as dimensional scores across six functional areas, thereby forming a bridge between the current diagnostic environment and the more research oriented RDoC framework. The proposed research focuses on transitioning the cMHQ and its outcomes from lab to marketplace to enable deeper clinical research insights and provide more informed treatment and referral regimens. In aim 1, we will build the cMHQ’s input assessment and diagnostic analysis by developing a responsive front-end assessment application and coding analysis scripts to generate data scoring metrics and diagnostic criteria. In aim 2, we will develop multiple data- output formats for the cMHQ that are tested for usability and acceptability, including an automatically generated cMHQ clinician report that provides a clear and comprehensive analysis of the patient’s mental health profile across multiple dimensions and disorders, as well as an API to enable tabular data outputs for integration into research systems. As part of this aim, we will also integrate all of the elements into a scalable architecture for testing and ensure HIPAA-compliance of the data-flow. If this project is successful, a further Phase 2 project will be warranted to pilot test its application in clinical research and practice domains to demonstrate the benefits to outcomes in both research and treatment.

抽象的 在此 SBIR 第一阶段提案中，我们的目标是开发工作流程并使其自动化，以实现全面的 跨诊断心理健康评估工具，可提高心理健康筛查的精确度。 目前使用的大多数仪器都是根据 DSM 标准设计的，该标准受到了批评 因为它是从理论上定义的，并且忽略了患者症状的异质性。 各个工具对同一疾病的症状的评估是不完整且异质的。 个体被置于预先定义的类别中，但这些类别并不反映他们的整体症状经历和生活 因素，并且诊断可能会根据工具的选择而有所不同，这使得诊断变得困难且耗时。 了解个体患者以确定治疗轨迹，有效招募患者参与研究试验， 并根据完整的症状表型了解结果 为了应对这些挑战， 新颖的评估工具 cMHQ 是由我们的合作伙伴非营利研究组织 Sapien 开发的 实验室，并提供全面的患者症状概况，涵盖 10 个基于 DSM 的心理健康 疾病以及六个功能领域的维度分数，从而在 当前的诊断环境和更多面向研究的 RDoC 框架。 专注于将 cMHQ 及其结果从实验室转移到市场，以实现更深入的临床研究 在目标 1 中，我们将建立 cMHQ 的意见并提供更明智的治疗和转诊方案。 通过开发响应式前端评估应用程序和编码来进行评估和诊断分析 用于生成数据评分指标和诊断标准的分析脚本 在目标 2 中，我们将开发多个数据 - cMHQ 的输出格式经过可用性和可接受性测试，包括自动生成的 cMHQ 临床医生报告对患者的心理健康状况提供清晰、全面的分析 跨多个维度和疾病，以及一个API，使表格数据输出能够集成到 作为这一目标的一部分，我们还将把所有元素集成到一个可扩展的架构中。 测试并确保数据流符合 HIPAA 如果该项目成功，将进行进一步的第 2 阶段项目。 有必要对其在临床研究和实践领域的应用进行试点测试，以证明其好处 研究和治疗的结果。