Deriving a Clinical Decision Rule for Suicide Risk in the Emergency Department Setting

得出急诊科自杀风险的临床决策规则

• 批准号: 10299606
• 负责人: Edwin D Boudreaux
• 金额: $ 84.37万
• 依托单位: UNIV OF MASSACHUSETTS MED SCH WORCESTER
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10299606
• 关键词: Accident and Emergency department; Address; Adopted; Adoption; Adult; Algorithms; Behavior; Behavioral; Blinded; Blunt Trauma; Cervical spine; Clinical; Confusion; Consultations; Data; Derivation procedure; Detection; Diagnostic; Economic Models; Electronic Health Record; Emergency Department Physician; Emergency Department patient; Emergency Department-based Intervention; Emergency Medicine; Emergency Nursing; Emergency Situation; Emergency department visit; Engineering; Enrollment; Ensure; Environment; Evaluation; Fright; Funding; Healthcare; In Situ; Individual; Industrialization; Industry Standard; Informatics; Injury; Inpatients; Interview; Joints; Literature; Machine Learning; Measures; Medical; Medical Records; Methods; Modeling; National Institute of Mental Health; Nurses; Outcome; Outpatients; Participant; Patient Care; Patients; Performance; Physicians; Predictive Analytics; Procedures; Prospective Studies; Psychologist; Published Comment; Research; Research Assistant; Research Personnel; Research Training; Resources; Risk; Risk Assessment; Safety; Sampling; Screening Result; Self-Direction; Stratification; Suicide; Suicide prevention; Sum; System; Testing; Training; Translations; Triage; Validation; Variant; Visit; base; clinical care; clinical practice; common rule; cost; design; economic cost; economic evaluation; effective intervention; electronic data; evidence base; evidence based guidelines; health care economics; high risk; implementation barriers; improved; indexing; inferential statistics; innovation; learning strategy; novel; prevent; risk stratification; screening; secondary outcome; simulation; suicidal behavior; suicidal patient; suicidal risk; trend

ABSTRACT Significance: As recent national controversy over Joint Commission mandates proves, universal suicide risk screening in emergency departments (ED) will not achieve widespread adoption because confusion remains around which specific risk indicators to assess, and clinicians fear that such screening will lead to massive surges in psychiatric evaluations. To address these two implementation barriers, the proposed study will derive a clinical decision rule to support universal risk detection and optimize patient care workflow in adult patients. Investigators: The Project Team has extensive expertise in ED-based suicide risk screening and assessment (Boudreaux, Larkin), clinical decision rule design (Boudreaux, Stiell), predictive analytics (Wang, Liu, Simon), machine learning and informatics (Liu, Simon), industrial engineering (Johnson), and healthcare economics (Clements). A Clinical Advisory Panel ensures that the proposal is grounded in the practical realities of the ED. Innovation: The proposed study will be the first to apply industry standards for deriving decision rules to suicide risk and will directly inform the controversy regarding the relative strengths and weaknesses of universal versus targeted screening. We will pioneer new statistical innovations for rule derivation and will integrate simulation of potential workflow impact using industrial engineering modeling and economic analyses. Approach: We have already developed a pool of empirically supported, clinician-acceptable candidate suicide risk indicators. Data on these candidate indicators will be collected by trained research staff on 500 adult medical patients and 500 adult psychiatric patients from a large ED. Participants will undergo a comprehensive suicide risk assessment by a research clinical psychologist blinded to the indicators who will assign the participant to a criterion reference risk group: Negligible, Mild-Moderate, or High risk. Participants will be followed for 24 weeks after the visit to assess suicidal behavior, our secondary outcome. In Aim 1, we will derive a universal screening decision rule for “all comers,” as well as a variant to be used with patients presenting with a psychiatric chief complaint (targeted). In Aim 2, we will test whether a previously validated risk stratification algorithm using data from the electronic health record improves the performance of the decision rules. In Aim 3, we will model the potential operational impact of the rules through dynamic modeling of clinical workflow and economic costs and assessing clinician and patient acceptability in a new sample of 100 ED clinician-patient dyads. Environment: UMass has demonstrated its capability to support this study through several key preliminary studies, including the ED-SAFE studies, System of Safety, and other suicide-related studies set in the ED. Impact: By providing clear, evidence-based recommendations on universal screening and optimized workflow using standards accepted by emergency clinicians, this study will address two pivotal barriers to universal suicide risk screening, transforming the “right thing” into the “easy thing” so it becomes the “usual thing.”

摘要 意义：正如最近全国对联合委员会授权的争议所证明的那样，普遍的自杀风险 在急诊科（艾德）进行筛查不会得到广泛采用，因为仍然存在混淆 围绕哪些具体的风险指标进行评估，临床医生担心这种筛查将导致大规模的 精神评估激增为了解决这两个实施障碍，拟议的研究将得出 临床决策规则，以支持通用风险检测和优化成人患者的患者护理工作流程。 研究者：项目团队在基于ED的自杀风险筛查和评估方面具有广泛的专业知识 （Boudreaux，Larkin），临床决策规则设计（Boudreaux，Stiell），预测分析（Wang，Liu，Simon）， 机器学习和信息学（刘，西蒙），工业工程（约翰逊）和医疗保健经济学 （克莱门茨）。一个临床咨询小组确保该建议是根据ED的实际情况。 创新：拟议的研究将是第一个应用行业标准来推导决策规则， 自杀风险，并将直接告知有关的相对优势和弱点的争议， 普遍筛查与靶向筛查。我们将开拓新的统计创新的规则推导，并将 使用工业工程建模和经济分析对潜在工作流程影响进行集成模拟。 方法：我们已经开发了一个经验支持的，临床医生可接受的候选自杀池 风险指标。关于这些候选指标的数据将由训练有素的研究人员收集， 医疗患者和500名来自大型ED的成年精神病患者。参与者将接受全面的 自杀风险评估由研究临床心理学家盲目的指标谁将分配 将受试者纳入标准参考风险组：可忽略、轻度-中度或高风险。参与者将被 随访24周后评估自杀行为，这是我们的次要结局。在目标1中，我们 为“所有来访者”推导出一个通用的筛查决策规则，以及一个用于患者的变体 提出精神病主诉（有针对性）。在目标2中，我们将测试先前验证的 使用来自电子健康记录的数据的风险分层算法提高了 决策规则。在目标3中，我们将通过动态建模对规则的潜在操作影响进行建模 临床工作流程和经济成本，并评估临床医生和患者的可接受性，在一个新的样本， 100例艾德临床医生-患者配对。 环境：麻省大学已经证明了它的能力，以支持这项研究，通过几个关键的初步 研究，包括ED-SAFE研究、安全系统和ED中设置的其他自杀相关研究。 影响：通过提供关于普遍筛查和优化工作流程的明确、循证建议 使用急诊临床医生接受的标准，这项研究将解决两个关键的障碍， 自杀风险筛查，把“正确的事情”变成“容易的事情”，使之成为“平常的事情”。