Fatal Overdose Review Teams - Research to Enhance Surveillance Systems (FORTRESS)
Fatal Overdose Review Teams - Research to Enhance Surveillance Systems (FORTRESS)
批准号:
10590303
负责人:
Matthew Aalsma
金额:
$157.1万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-09-30 至 2024-09-29
关键词:
AddressAdherenceAffectAttitudeCenters for Disease Control and Prevention (U.S.)Cessation of lifeChargeChildChildhoodCollectionCommunitiesCountyDataData AggregationDecision MakingDevelopmentDrug usageEnsureEpidemicEventEvidence based treatmentGoalsGuidelinesHarm ReductionHealthHelping to End Addiction Long-termImprisonmentIndianaIndividualInterventionInterviewLeadLegalLinkModelingOpiate AddictionOpioidOutcomeOverdoseOverdose reductionPerformancePharmaceutical PreparationsPharmacotherapyPhasePhilosophyPilot ProjectsPolicy MakingPopulationPractice GuidelinesPrevention strategyPublic HealthPublic Health PracticeRandomizedRecommendationRecording of previous eventsResearchResearch DesignResourcesRisk FactorsRuralServicesSocial WorkSourceSpeedSumSurveysSystemTestingTimeTrainingTranslatingUnited States National Institutes of Healthbasecomorbiditycontextual factorsdashboarddata infrastructuredata repositorydesigneffectiveness outcomeemotional traumaevidence baseimplementation outcomesimplementation processimprovedmembermortalitymultidisciplinarymultiple data sourcesneglectopioid misuseoverdose deathoverdose preventionoverdose riskprogramsservice gapsocialsuccesssystems researchtime usetooltrial comparinguptakeusabilityuser centered design
中文摘要
这项研究是NIH帮助结束成瘾长期(Hear)倡议的一部分,该倡议旨在加快科学解决国家阿片类药物公共健康危机的速度。NIH Hear Initiative支持整个NIH的研究,以改善阿片类药物滥用和成瘾的治疗,并制定能够为阿片类药物危机提供快速和持久解决方案的具体战略。
该项目寻求通过与过量用药死亡审查(OFR)小组合作来解决过量用药流行问题。目前OFR的做法依赖于个案审查模式来提出政策和方案建议。然而,过量服药率的持续上升和可预防的过量死亡人数表明
需要将OFR团队从病例审查转移到使用及时的人口层面数据,以更好地为他们的建议和行动提供信息。我们提议的项目--致命过量审查小组--加强监测系统的研究(堡垒)的目标是通过为OFR配备以下设备来改进标准的OFR实践
数据仪表板建立在实时汇总数据的基础上,跨多个来源进行记录链接,并以一种有助于识别和可视化常见的“过量接触点”的方式呈现,或提供减少伤害服务的机会,或让有过量服药风险的个人参与循证治疗。与世界银行的目标保持一致
根据Hear Data2行动计划,堡垒研究团队将利用现有资源和专业知识帮助OFRS将数据转化为行动。在R61阶段,研究小组将加强与两个州机构--印第安纳州卫生部和印第安纳州管理层--建立的跨部门伙伴关系
Performance Hub(MPH),提供必要的全州数据基础设施,以记录和链接来自多个来源的人口级别的管理数据。公共卫生部门还成功地开发了可供公众访问的数据仪表板。堡垒团队将在MPH早期成功的基础上,确保更及时地收集服药过量事件数据,并设计“服药过量触点仪表板”(AIM 1)。我们的团队将培训OFR团队成员进行数据驱动决策(DDDM),以有效使用仪表板。堡垒团队还包括参与制定疾控中心OFR最佳实践指南的个人,以及对OFR遵守这些指南的试点研究,这将为我们团队开发“OFR Fidelity Tool”(目标2)提供信息。该工具将是此类工具中的第一个。对于R33阶段,我们将进行整群随机阶梯楔形试验,比较我们的干预(仪表板+DDDM培训)与标准OFR做法对实施(目标3)和有效性结果(目标4)的影响。执行成果包括执行
流程忠诚度(实施完成阶段)、工作人员对减少危害理念的接受度(定性访谈)、OFR对疾控中心最佳实践的忠诚度(堡垒OFR Fidelity工具)以及过量使用Touchpoint Dashboard的可用性(系统可用性量表)。全州范围的OFR数据存储库充当丰富的
有效性结果的数据来源,包括OFR团队建议的质量和实施建议的过量用药预防战略的当地行动。我们还将对OFR团队成员进行调查,以评估他们对循证过量预防策略态度的变化。总而言之,堡垒团队是唯一有资格帮助OFRS使用更全面、可用的数据来为减少过量用药提供高质量、面向行动的建议的机构。
英文摘要
This study is part of the NIH’s Helping to End Addiction Long-term (HEAL) initiative to speed scientific solutions to the national opioid public health crisis. The NIH HEAL Initiative bolsters research across NIH to improve treatment for opioid misuse and addiction and to develop concrete strategies capable of providing rapid and durable solutions to the opioid crisis.
This project seeks to address the overdose epidemic by working with overdose fatality review (OFR) teams. Current OFR practices rely on the case review model to make policy and programmatic recommendations. However, the continued rise in overdose rates and sheer number of preventable overdose deaths suggest a
need to shift OFR teams away from case review and toward using timely population-level data to better inform their recommendations and actions. The goal of our proposed project, Fatal Overdose Review Teams – Research to Enhance Surveillance Systems (FORTRESS), is to improve standard OFR practices by equipping OFRs with
a data dashboard built on real-time aggregate data, record-linked across multiple sources and presented in a way that helps identify and visualize common “overdose touchpoints,” or opportunities to deliver harm-reduction services or engage individuals at risk for overdose in evidence-based treatment. Aligning with the goals of the
HEAL Data2Action Program, the FORTRESS research team will leverage available resources and expertise to help OFRs translate data to action. During the R61 Phase, the research team will strengthen established cross-sector partnerships with two state agencies, the Indiana Department of Health and the Indiana Management
Performance Hub (MPH), which provide the necessary statewide data infrastructure to record-link population-level administrative data from multiple sources. MPH has also successfully developed publicly accessible data dashboards. The FORTRESS team will build on the early successes of MPH to ensure more timely collection of overdose event data and design the “Overdose Touchpoints Dashboard” (Aim 1). Our team will train OFR team members in Data-Driven Decision Making (DDDM) to effectively use the dashboard. The FORTRESS team also includes individuals involved in developing the CDC’s OFR best practice guidelines and a pilot study of OFR adherence to these guidelines, which will inform our team’s development of an “OFR Fidelity Tool” (Aim 2). This tool will be the first of its kind. For the R33 phase, we will conduct a cluster-randomized stepped-wedge trial comparing the impact of our intervention (dashboard + DDDM training) versus standard OFR practices on both implementation (Aim 3) and effectiveness outcomes (Aim 4). Implementation outcomes include implementation
process fidelity (Stages of Implementation Completion), staff acceptance of harm reduction philosophies (qualitative interviews), OFR fidelity to CDC best practices (FORTRESS OFR Fidelity Tool), and usability of the Overdose Touchpoint Dashboard, (Systems Usability Scale). A statewide OFR data repository serves as a rich
source of data on effectiveness outcomes, including OFR team recommendation quality and local actions to implement recommended overdose prevention strategies. We will also survey OFR team members to assess changes in their attitudes toward evidence-based overdose prevention strategies. In sum, the FORTRESS team is uniquely qualified to help OFRs use more comprehensive, available data to inform quality, action-oriented recommendations to reduce overdose.
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