Computerized Adaptive Suicidal Risk Stratification and Prediction

计算机化自适应自杀风险分层和预测

基本信息

批准号：
10254382
负责人：
Edwin D Boudreaux
金额：
$ 74.66万
依托单位：
ADAPTIVE TESTING TECHNOLOGIES
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-05-01 至 2024-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10254382
关键词：
Accident and Emergency department Address Adoption Adult Architecture Behavior Blinded Caring Cessation of life Clinical Computer software Data Data Store Databases Detection Electronic Health Record Elements Emergency Department patient Emergency department visit Enrollment Ensure Environment Equation Evaluation Feedback Foundations Funding Health Personnel Health system Healthcare Healthcare Systems Individual Injury Intake Intervention Interview Intuition Literature Location Machine Learning Manuals Massachusetts Measurement Measures Medical Mental Health Mental Tests Methods Monitor National Institute of Mental Health Participant Patient Outcomes Assessments Patient Self-Report Patient-Focused Outcomes Patients Performance Phase Play Production Protocols documentation Psychometrics Psychopathology Publishing Research Research Assistant Research Training Risk Risk Assessment Sampling Schedule Screening procedure Self-Direction Severities Small Business Innovation Research Grant Standardization Structure Suicide Suicide prevention System Tablets Testing Time Travel United States Universities Violence Visit Work advanced analytics base brief intervention clinical decision support clinical decision-making computerized data visualization design flexibility handheld mobile device health care settings improved indexing innovation instrument learning strategy patient population point of care professor programs psychiatric emergency risk prediction risk prediction model risk stratification screening secondary outcome substance misuse suicidal suicidal behavior suicidal risk suicide model systematic review usability user centered design

项目摘要

ABSTRACT In the next 60 minutes, at least 57 people in the United States (US) will attempt to kill themselves, and five will die. Over 80% of these individuals encountered a healthcare provider in the 12 months before his or her death, but their risk will have gone undetected or, if detected, poorly quantified and not sufficiently monitored longitudinally. The proposed research will address this deficit by building and validating the Computerized Adaptive Test for Suicide Scale -- Expanded (CAT-SS EXPANDED), software that can screen for, quantify, and monitor suicide risk in a way far superior to existing instruments. It will enable at least three key Zero Suicide performance elements, including systematic, standardized frontline suicide risk screening and measurement (Identify), tracking and communicating risk across locations of care (Transitions), and monitoring changes in patient outcomes resulting from continuous quality improvement activities (Improve). In a paradigm shifting innovation, the CAT-SS EXPANDED will not only comprise the first multi-dimensional CAT of its kind, it will import suicide risk indicators that have already been validated by the NIMH-funded Mental Health Research Network (MHRN) directly from a health system’s electronic health record (EHR). This SBIR Fast Track has two phases. Phase 1 will build the CAT-SS EXPANDED, starting with well-established preliminary work and using iterative user testing with 20 clinician-patient dyads to refine the features. Phase 2 will have two Aims. The first Aim will validate the CAT-SS EXPANDED against an independent research clinician’s suicide risk stratification and suicidal behavior 24 weeks after the index visit (n=700). The second Aim will complete two-way integration of the validated CAT-SS EXPANDED into UMass’ EHR production environment and will evaluate clinical usability and acceptability with a new sample of ~30 suicide-risk enriched patients. Innovation and Impact: While traditional suicide screening tools exist, they are very limited, a conclusion supported by systematic reviews, the National Action Alliance for Suicide Prevention, and the NIMH. Because of these limitations, strong, well-validated clinical decision support to guide appropriate levels of care do not exist, reinforcing non-standardized and inefficient workflow, such as a tendency to conservatively order unnecessary emergency psychiatric evaluations. The CAT-SS EXPANDED will address these well-known measurement limitations using cutting edge strategies embodied in multi-dimensional CAT and EHR-derived risk indicators, an unprecedented capability impossible to achieve with existing measures. While this study focuses on the ED as a starting point because of its well-known risk burden and emerging literature supporting the value of universal suicide risk screening combined with brief interventions, the CAT-SS EXPANDED will be specifically designed and later tested as the first approach to suicide risk monitoring suitable for enterprise deployment across settings and locations of care, which is transformational for suicide prevention and fundamental to the Zero Suicide model’s emphasis on holistic system change.

抽象的在接下来的60分钟内，美国至少有57人（美国）将尝试自杀，五人将死。这些人中有80％在他或她去世前的12个月中遇到了医疗保健提供者但是他们的风险将未被发现，或者，如果检测到的，量化不佳且未得到足够的监控纵向。拟议的研究将通过构建和验证计算机化来解决此辩护自杀量表的自适应测试 - 扩展（CAT-SS扩展），可以筛选，量化，并以远比现有工具优越的方式监视自杀风险。它将至少启用三个键零自杀绩效要素，包括系统的，标准化的前线自杀风险筛查和测量（识别），跟踪和交流护理位置（过渡）的风险以及监视持续质量改善活动（改进）导致患者结局的变化。在范式中转移创新，Cat-SS扩展将不仅包括同类的第一只多维猫将进口已通过NIMH资助的心理健康验证的自杀风险指标直接来自卫生系统的电子健康记录（EHR）的研究网络（MHRN）。这个sbir很快轨道有两个阶段。第一阶段将构建CAT-SS扩展，从建立的初步开始使用20个临床患者二元组来工作并使用迭代用户测试来完善这些功能。第二阶段将有两个目标。第一个目的将验证CAT-SS扩大针对独立研究临床的扩展指数访问后24周后自杀风险分层和自杀行为（n = 700）。第二个目标已验证的CAT-SS的完全双向整合扩展到UMass的EHR生产环境并将通过〜30个自杀风险富含患者的新样本来评估临床可用性和可接受性。创新和影响：尽管存在传统的自杀筛查工具，但它们非常有限，这是一个结论在系统评价，国家预防自杀行动联盟和NIMH的支持下。因为在这些限制中，强大，验证良好的临床决策支持以指导适当的护理水平存在，加强非标准和效率低下的工作流程，例如保守秩序的趋势不必要的紧急精神病评估。 Cat-Ss扩展将解决这些著名的使用在多维CAT和EHR衍生的尖端策略的测量限制风险指标，现有测量结果无法实现的前所未有的能力。这项研究专注于ED作为起点，因为伯恩（Burnen）和新兴文献支持普遍自杀风险筛查的价值与简短的干预措施相结合，CAT-SS扩大将是专门设计和后来测试是适用于企业的自杀风险监控的第一种方法跨护理设置和位置的部署，这是预防自杀和零自杀模型的重点是整体系统变化的基础。