C-DIAS RP 1: A community-driven modeling approach for identifying and implementing evidence-based interventions and implementation strategies to reduce overdose deaths.

C-DIAS RP 1：社区驱动的建模方法，用于确定和实施循证干预措施和实施策略，以减少用药过量死亡。

• 批准号: 10493959
• 负责人: C. HENDRICKS BROWN
• 金额: $ 57.05万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10493959
• 关键词: Accident and Emergency department; Address; Adopted; Adoption; Affect; Behavior; COVID-19 pandemic; Caring; Cessation of life; Communities; Complex; Country; County; Criminal Justice; Data; Decision Making; Decision Support Model; Decision Support Systems; Dissemination and Implementation; Epidemiology; Evidence based intervention; Evidence based practice; Failure; Feedback; Florida; Funding; Geographic state; Heart; Homelessness; Hospitalization; Human Resources; Individual; Influentials; Intervention; Interview; Knowledge; Learning; Local Government; Location; Measures; Mediation; Methodology; Methods; Minority; Modeling; Monitor; Opioid; Outcome; Output; Overdose; Overdose reduction; Persons; Pharmaceutical Preparations; Phase; Policy Maker; Population; Process; Public Health; Recovery; Research; Research Personnel; Research Project Grants; Resources; Risk; Services; Specific qualifier value; Standardization; Stimulant; Stimulant overdose; Surface; Surveys; System; Testing; Time; To specify; Training; Universities; addiction; base; community based participatory research; contextual factors; contingency management; cost; data harmonization; design; effective therapy; epidemiologic data; experimental study; falls; flexibility; implementation context; implementation outcomes; implementation process; implementation strategy; improved; innovation; models and simulation; mortality; novel therapeutics; open data; opioid overdose; opioid use; overdose death; programs; response; service providers; simulation; standardize measure; stimulant use disorder; substance use treatment; support tools; tool; trustworthiness

C-DIAS RESEARCH PROJECT 1: PROJECT SUMMARY/ABSTRACT While effective treatments exist, and substantial new funding has been distributed to states and territories to expand access, the US continues to be plagued with opioid and stimulant related deaths. Nonlethal overdoses, emergency room and hospitalization utilization also continue to escalate. Research Project 1 proposes to develop an innovative model-driven decision support system to aid counties to prioritize and optimize the use of available resources to address opioid and stimulant deaths. This new implementation strategy differs from and extends data-driven decision making, which by itself does not produce information on projected impact. In particular, this system examines a multitude of different options for implementation strategies that fit a county’s needs and capacities, and identifies optimal solutions that are robust to changing contexts. This model-driven decision support (MDDS) implementation strategy integrates three components: 1) an ongoing community- research partnership, which is essential if decision makers are to feel the predictions are locally relevant and trustworthy; 2) integrated administrative, interview, and survey data, which are required to account for the locally unique contextual factors; and 3) a modular agent-based model (ABM) that integrates data, represents alternative implementation strategies, and simulates their behavior on overdose deaths under varying conditions. The first aim focuses on extending an existing ABM that takes as input local data and produces projections across diverse strategies’ impact on overdose deaths and disparities. Response surface methodology and mediation modeling are used to summarize findings. Front-end tools are developed along with training so the system can be used by other counties. The second aim examines the generalizability of this approach in three diverse counties: Pinellas County FL, Vermilion County IL, and Santa Clara County CA. We have active partnerships with all three communities. If there is no change in mortality in these 3 counties, more than 3,000 individuals are expected to die from overdose in the coming 5 years. The third aim focuses on advancing an approach for improving care through monitoring and feedback, both within these communities and across using a learning collaborative. This aim also formally evaluates the MDDS using the Stages of Implementation Completion (SIC) as well as measuring acceptability and the degree to which the communities are using this approach differently from one based on data only. At the PREPARE phase of the implementation process, Research Project 1 is bi-directionally integrated with C-DIAS, and uses common measures with the other C-DIAS Research Projects. In pursuit of C-DIAS specific aim 2, in concert with the Research Core, this project will serve as a vehicle to test and advance ABM and cost modeling decision supports for policymakers and implementation endeavors nationwide. Project findings will be widely influential because of C-DIAS dissemination platforms, including open science assess to ABM tools, resulting in greater impact than otherwise possible if conducted independently.

C-dias研究项目1：项目摘要/摘要