Evaluating Effectiveness and Implementation of a Risk Model for Suicide Prevention Across Health Systems

评估跨卫生系统自杀预防风险模型的有效性和实施

基本信息

批准号：
10689266
负责人：
BobbiJo H. Yarborough
金额：
$ 76.94万
依托单位：
KAISER FOUNDATION RESEARCH INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-23 至 2026-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10689266
关键词：
Acceleration Address Adopted Adult Bioinformatics Caring Clinic Clinical Clinical Data Collaborations Computer Models Data Effectiveness Electronic Health Record Elements Emergency Situation Ensure Failure Feedback Funding Health Health Care Visit Health Insurance Health Services Health system Healthcare Hybrids Individual Inpatients Intervention Leadership Measures Medicare/Medicaid Mental Health Michigan Minnesota Modeling Monitor Movement National Institute of Mental Health Oregon Outcome Outpatients Patient Self-Report Patients Pilot Projects Population Heterogeneity Prevention approach Process Process Assessment Public Health Questionnaires Randomized Reach, Effectiveness, Adoption, Implementation, and Maintenance Research Resolution Risk Services Severities Site Suicide Suicide attempt Suicide prevention System Testing United States Washington advanced system behavioral health clinical application clinical implementation cost data infrastructure design effectiveness evaluation effectiveness measure effectiveness outcome effectiveness/implementation trial health care settings health record implementation design implementation evaluation implementation outcomes implementation questions improved innovation instrument insurance claims interest medical specialties member patient population pragmatic implementation pragmatic trial preference prevent prevention service reducing suicide response risk prediction screening service engagement statistics suicidal risk suicide model time use tool treatment as usual trial design

项目摘要

PROJECT SUMMARY/ABSTRACT: Suicide is a major public health concern in the United States; nearly 50,000 individuals die by suicide annually and almost 1.5 million attempt suicide. To date, identification of individuals at risk for suicide has relied on suicide risk screening practices, including using a variety of self- report instruments. However, sensitivity of these measures are only moderate; more precise tools for identifying patients at risk for suicide are needed. Suicide risk models, developed by our team, incorporate health records data and historical self-report screening questionnaire responses to improve accuracy of risk prediction. Our models have outperformed traditional clinical screening and similar risk models for adults receiving care in outpatient mental health specialty settings. However, while accurate, they have not been evaluated in real world care; whether the models actually increase identification or result in patients receiving more suicide prevention services, fewer crisis services, or making fewer suicide attempts is unknown. There is substantial clinical interest in implementing suicide risk models but little scientific evidence about the effectiveness of these models in real world settings compared to standard screening practices alone. Additionally, there is almost no guidance for their implementation in healthcare. The proposed project leverages the NIMH-funded Mental Health Research Network (MHRN), a collaboration of large health systems with established clinical data infrastructure to support multi-site studies. MHRN members Henry Ford Health System, Kaiser Permanente Northwest, and HealthPartners will participate in this project and collectively serve >170,000 behavioral health patients per year. The patient populations are diverse, including thousands of individuals with Medicaid and Medicare. Each of these systems has implemented a suicide prevention care model in their behavioral health departments, including robust suicide risk screening and assessment processes. However, none of these systems has implemented a suicide risk model. The proposed project includes a pragmatic trial approach with randomization of behavioral health clinics across the three participating health systems. It is innovative because it seeks to implement an MHRN suicide risk model (intervention) into each system's existing suicide prevention care model (usual care) to increase the reach and effectiveness of the suicide prevention care models. Sites will receive implementation planning support based on stakeholder feedback from preliminary studies and deliverables include an implementation planning tool kit to facilitate spread. This high-impact study has important clinical implications as health systems consider whether it makes sense to enhance their existing suicide prevention care models with a suicide risk model. It is timely because many health systems are advancing toward suicide risk model implementation without evidence to support this innovation.

项目摘要/摘要：自杀是美国的一个主要公共卫生问题；几乎每年有 50,000 人死于自杀，近 150 万人试图自杀。迄今为止，鉴定有自杀风险的个人依赖于自杀风险筛查做法，包括使用各种自我评估方法报告文书。然而，这些措施的敏感性仅为中等；更精确的工具需要识别有自杀风险的患者。我们团队开发的自杀风险模型包含健康记录数据和历史自我报告筛查问卷答复，以提高风险的准确性预言。我们的模型优于传统的临床筛查和类似的成人风险模型在门诊心理健康专业机构接受护理。然而，虽然准确，但它们并未被在现实世界的护理中进行评估；这些模型是否确实增加了识别或导致患者接受更多的自杀预防服务、更少的危机服务或更少的自杀企图都是未知的。那里对实施自杀风险模型有很大的临床兴趣，但关于自杀风险模型的科学证据很少与单独的标准筛选实践相比，这些模型在现实世界中的有效性。此外，几乎没有关于其在医疗保健领域实施的指导。拟议项目利用 NIMH 资助的心理健康研究网络 (MHRN)，该网络是大型医疗机构的合作项目具有已建立的临床数据基础设施的系统来支持多站点研究。 MHRN 成员亨利福特医疗系统、Kaiser Permanente Northwest 和 HealthPartners 将参与该项目，每年总共服务超过 170,000 名行为健康患者。患者群体多种多样，包括数千名享受医疗补助和医疗保险的个人。这些系统中的每一个都实现了行为健康部门的自杀预防护理模式，包括强有力的自杀风险筛查和评估流程。然而，这些系统都没有实现自杀风险模型。这拟议的项目包括一种务实的试验方法，将行为健康诊所随机化三个参与的卫生系统。它具有创新性，因为它旨在实施 MHRN 自杀风险将模型（干预）纳入每个系统现有的自杀预防护理模型（常规护理）中，以增加自杀预防护理模式的覆盖范围和有效性。站点将收到实施计划基于利益相关者对初步研究和可交付成果的反馈的支持，包括实施规划工具包以促进传播。这项高影响力的研究对于健康具有重要的临床意义系统考虑通过以下方式增强现有的自杀预防护理模式是否有意义：自杀风险模型。这是及时的，因为许多卫生系统正在向自杀风险模型迈进实施没有证据支持这一创新。