Reducing Drug-Related Mortality Using Predictive Analytics: A Randomized, Statewide, Community Intervention Trial
Reducing Drug-Related Mortality Using Predictive Analytics: A Randomized, Statewide, Community Intervention Trial
批准号:
10026087
负责人:
Magdalena Cerda
金额:
$65.41万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-30 至 2024-07-31
关键词:
Academic DetailingAddressAdmission activityAmericanAreaBuprenorphineCensusesCitiesClassificationCommunitiesCommunity PharmacyDataDecision MakingDisease OutbreaksDoseEmergency medical serviceEnvironmentEpidemicFutureGoalsHealthHealth PrioritiesHospitalsInstitutionInterventionIntervention Community TrialIntervention TrialLightMachine LearningMethadoneModelingMorbidity - disease rateNaloxoneNational Institute of Drug AbuseNeighborhoodsOverdosePharmaceutical PreparationsPhasePoliciesPopulationPredictive AnalyticsPreventionPrevention programPreventive InterventionProbabilityPublic HealthPublishingRandomizedRecording of previous eventsRecordsRecoveryResearch PriorityResource AllocationResourcesRhode IslandRiskServicesSourceStrategic PlanningSumSystemTestingUnited StatesVisitWorkaddictionbaseevidence baseexperienceexperimental studyhigh riskimprovedindexingmachine learning methodmortalitynovelopioid agonist therapyopioid misuseopioid mortalityopioid overdoseopioid policyopioid use disorderoverdose deathoverdose preventionoverdose riskpeerpopulation basedprediction algorithmpredictive modelingprescription opioidpreventprimary outcomeprogramspublic health prioritiesreferral servicesresource guidesresponsespatiotemporalsurveillance datatooltreatment arm
中文摘要
项目摘要
自1999年以来,美国的过量死亡人数急剧上升。这一流行病引起了广泛的
联邦和州政府采取了行动,但死于吸毒过量的人数仍在继续增加。鉴于
加速和迅速演变的过量流行病,需要新的战略,以确定社区
我们呼吁各国政府采取措施,确保最易受危害的人的健康,并更有效地利用资源,遏制过量用药造成的死亡。为了解决这些公共卫生问题,
优先事项,我们将开发一种预测工具,在过量死亡发生之前预测它们,然后进行
随机,全州,社区一级的干预,以评估资源的目标,根据这些
预测。这项研究将在罗得岛进行,该州是美国吸毒过量死亡率第10高的州。
2016.研究分两个阶段。首先,我们将开发一个预测分析模型,
过量死亡率在社区一级,使用公开的信息和数据,从一个
多组分过量监测系统。这种工具,称为PROVIDENT(预防过量使用
环境信息和数据)将被用于预测未来的可能性
罗得岛每个社区都有吸毒过量死亡的案例接下来,我们将进行随机化的政策
实验,以评估是否有针对性的过量预防干预措施,以最高风险的社区
减少过量的发病率和死亡率。州卫生部将收到PROVIDENT模型
罗得岛39个城镇中有一半的预测。在这些城市/城镇,卫生部门将
与利益相关者合作,将过量预防干预措施的目标锁定在
未来过量死亡的可能性。干预措施包括努力:(1)防止高风险处方
(通过学术详述和其他教育工作);(2)扩大阿片类激动剂治疗的可及性,
包括丁丙诺啡和美沙酮;(3)增加纳洛酮分布(通过社区和
(4)扩大街头同伴康复辅导和转介。控制
城市/城镇将继续接受这些干预措施,但不针对具体的社区。致命
对照城市/城镇的非致命性阿片类药物过量率将与接受
提供模型预测。为了实现这些目标,我们将利用一个独特的伙伴关系,
学术机构和国家卫生部门,这使得前所未有的访问和共享
基于人群的过量用药监测数据。我们的研究结果将改善公共卫生决策,
向应作为循证预防、治疗
康复和过量抢救服务如果发现有效,PROVIDENT预测模型将
向其他国家传播,这些国家可以调整这一工具,以指导资源分配,
健康影响。总之,该项目高度响应了国家研究所的一项首要研究重点,
药物滥用,并直接解决国家最具挑战性的公共卫生危机之一。
英文摘要
PROJECT SUMMARY
Overdose deaths have skyrocketed in the United States since 1999. The epidemic has prompted widespread
federal and state actions, yet the number of people who die of an overdose continues to increase. In light of
the accelerating and rapidly evolving overdose epidemic, new strategies are needed to identify communities
most at risk, and to utilize resources more effectively to curb overdose deaths. To address these public health
priorities, we will develop a forecasting tool to predict overdose deaths before they occur, and then conduct a
randomized, statewide, community-level intervention to evaluate resource targeting based on these
predictions. The study will take place in Rhode Island, a state with the 10th highest rate of overdose fatality in
2016. The study has two phases. First, we will develop a predictive analytics model that forecasts future
overdose mortality at the neighborhood-level, using publicly available information and data from a
multicomponent overdose surveillance system. This tool, called PROVIDENT (Preventing Overdose using
Information and Data from the Environment) will be used to predict the likelihood of magnitude of future
overdose deaths in every neighborhood across Rhode Island. Next, we will conduct a randomized policy
experiment to evaluate whether targeting overdose prevention interventions to neighborhoods at highest risk
reduces overdose morbidity and mortality. The state's department of health will receive PROVIDENT model
predictions for half of the 39 cities/towns in Rhode Island. Within these cities/town, the health department will
work with stakeholders to target overdose prevention interventions to neighborhoods with the highest
probability of future overdose deaths. Interventions include efforts to: (1) prevent high-risk prescribing
(through academic detailing and other educational efforts); (2) expand access to opioid agonist therapy,
including buprenorphine and methadone; (3) increase naloxone distribution (through community and
pharmacy-based efforts); and (4) expand street-based peer recovery coaching and referrals. Control
cities/town will continue to receive these interventions, but without targeting to specific neighborhoods. Fatal
and non-fatal opioid overdose rates in the control cities/towns will be compared to those that received the
PROVIDENT model predictions. To achieve these aims, we will leverage a unique partnership between an
academic institution and a state's health department, which allows for unprecedented access to and sharing
of population-based overdose surveillance data. Our results will improve public health decision-making and
inform resource allocation to communities that should be prioritized for evidence-based prevention, treatment,
recovery, and overdose rescue services. If found to be effective, the PROVIDENT forecasting model will be
disseminated to other states, which could adapt the tool to guide resource allocation and maximize public
health impact. In sum, this project is highly responsive to a top research priority of the National Institute on
Drug Abuse, and directly addresses one of the nation's most challenging public health crises.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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海外基金