Participatory System Dynamics for Evidence-based Addiction and Mental Healthcare

项目总结/摘要 我们的总体长期目标是确定有效的严格的、可扩展的实施创新 改善医疗保健系统中循证实践（EBP）的实施。创伤后应激障碍抑郁症 和物质使用障碍是非常普遍和衰弱的，是退伍军人寻求护理的主要原因 退伍军人健康管理局（VA）。尽管投资增加EBP采用这些疾病 在提供者中，EBP在接收时间上有很大的差异，在门诊病人中的覆盖范围有限 人口如果不改善及时获得高质量服务的机会，心理健康状况未得到满足的退伍军人， 成瘾需要有慢性损害和死亡的风险。EBP需要协调多个预约 在多学科服务交付团队和跨通才和专业计划。重新设计 相互依赖的流程，如调度实践、转诊程序、患者流和人员配备 拨款必须因地制宜，需要利益攸关方的大力支持和支持。作为一个 在这一领域，实施科学必须超越对系统障碍和促进因素的描述，以解决这一问题。 系统复杂性通过对利益相关者进行三角测量，渐进式系统动力学建模满足了这一需求 观点，行政数据和模型模拟，赋予有关的严谨性和具体性， EBP实施在当地环境中有效或无效的机制。我们的短期目标 评估参与式系统动力学建模是否有助于改善EBP的时间和范围， 由于资源和复杂性（高与低）的差异而选择的VA门诊系统。VA 专家，当地领导人和供应商，以及有精神健康和成瘾患者经验的退伍军人 参与建模过程，以解决多维EBP交付动态。模型测试利益相关者 关于改进策略的假设，并正式指定系统实现备选方案的能力 考虑到当地的限制。模型模拟评估新的EBP政策或程序的系统影响 在实施之前，与试错法相比节省时间和资源。行政 在模型中合成数据，并使其对开发特定场地的利益相关者具有新的可操作性 重组计划。有效性目标测试：1）扩大EBP在患者人群中的覆盖范围，以及 2)在12个月的随访期内，与12个月前相比，从摄入到EBP的时间缩短 建模/重新设计。扩展系统动力学建模为实施科学家带来了希望 寻求创新方法，让利益相关者更准确地理解EBP交付 改善执行成果的动态和背景。如果被证明是有效的，参与式系统 动态建模可以用来解决改进电子商务计划实施战略的迫切需要， 卫生服务系统，从而有助于满足国家优先事项，以确保及时、高质量的卫生保健。

PROJECT SUMMARY / ABSTRACT Our overarching, long-range goal is to identify rigorous, scaleable implementation innovations that are effective for improving the implementation of evidence-based practices (EBP) in healthcare systems. PTSD, depression and substance use disorders are highly prevalent and debilitating, and are primary reasons Veterans seek care in the Veterans Health Administration (VA). Despite investment in increasing EBP adoption for these disorders among providers, EBPs have wide variability in time-to-receipt and limited reach among the outpatient population. Without improving timely access to high-quality services, Veterans with unmet mental health and addiction needs are at risk for chronic impairment and death. EBPs require multiple appointments coordinated within multidisciplinary service delivery teams and across generalist and specialty programs. Redesigning interdependent processes, such as scheduling practices, referral procedures, patient flows, and staffing allocations must be locally tailored and require considerable stakeholder buy in and support. To advance as a field, implementation science must move beyond descriptions of system barriers and facilitators to address this system complexity. Participatory system dynamics modeling meets this need by triangulating stakeholder perspectives, administrative data and model simulations, conferring rigor and specificity regarding the mechanisms by which EBP implementation is effective or ineffective in local settings. Our short-term objective is to evaluate whether participatory system dynamics modeling helps to improve EBP timing and reach in two VA outpatient systems that were selected due to differences in resources and complexity (high vs. low). VA experts, local leaders and providers, and Veterans with experience as mental health and addiction patients engage in a modeling process to address multidimensional EBP delivery dynamics. Models test stakeholder hypotheses about improvement strategies and formally specify system capacity for implementation alternatives accounting for local constraints. Model simulations evaluate system impacts of new EBP policies or procedures prior to implementation, saving time and resources as compared to trial-and-error approaches. Administrative data is synthesized in models and made newly actionable to stakeholders who develop site-specific restructuring plans. Effectiveness aims test for: 1) increased reach of EBPs among the patient population, and 2) reduced time from intake to EBP, over a 12-month follow-up period, as compared to twelve months before modeling/redesign. Participatory system dynamics modeling holds promise for implementation scientists seeking innovative methods for engaging stakeholders around more precise understandings of EBP delivery dynamics and context to improve implementation outcomes. If shown to be effective, participatory system dynamics modeling can be used to address the critical need for strategies that improve EBP implementation in health service systems, and thereby, help to meet national priorities to ensure timely, high-quality health care.