Participatory system dynamics vs usual quality improvement: Is staff use of simulation an effective, scalable and affordable way to improve timely Veteran access to high-quality mental health care?

背景：循证实践(EBP)是满足退伍军人最高价值的治疗方法 成瘾和心理健康需求，减少慢性损害，防止自杀或过量用药。超过10 多年来，退伍军人事务部投资于传播循证心理疗法和药物疗法 与通常的护理相比，有大量有效的证据。质量指标还跟踪进度。 尽管有这些投资，有普遍需求的患者，如抑郁症、创伤后应激障碍和阿片类药物的使用 失调症患者通常不会收到EBP。系统理论将有限的EBP覆盖范围解释为一种系统行为 动态地从本地组件(例如，患者需求/健康服务供应)中出现。参与式 研究和参与原则指导参与式系统动力学(PSD)，这是一种混合方法 在业务和工程中使用的方法，被证明是有效地提高现有质量的方法 资源。意义/影响：我们提出了我们在退伍军人成瘾和心理方面的高度优先领域的研究 医疗保健，以改善退伍军人获得退伍军人管理局最高质量医疗服务的机会。我们的PSD计划，从建模到学习 (MTL)，通过模拟人员配备、调度 以及医疗保健中常见的跨全科医生和专科计划、患者群体、 以及提供者的纪律/治疗。创新：最近在企业范围的SQL中合成了VA数据 企业数据仓库(CDW)使扩展参与式模拟学习活动成为可能 退伍军人管理局前线成瘾和心理健康工作人员。MTL是一种高级质量改进(QI)基础设施 这有助于退伍军人管理局向成为一个学习型医疗保健系统迈出重要一步，通过赋予当地 多学科工作人员制定适合当地能力和制约因素的改革战略。型号 参数来自一个VA来源，并在卫生服务中通用。如果调查结果显示MTL是 优于通常与退伍军人管理局计划办公室的协调员一起进行的退伍军人事务部质量改进活动， 事实证明，这种模式在退伍军人管理局服务中很有用。可持续发展战略方针还推动了执行 科学。系统论解释了动态系统行为(EBP范围)是如何由一般定义的 科学定律，但产生于具体的当地情况。通过系统科学模拟增强员工的能力 鼓励对学习所需的想法进行安全的原型设计，提高持续的质量改进 与试错法相比，它具有更高的处理能力，节省了时间和金钱。具体目标：1. 有效性：测试MTL在增加患者比例方面优于常规QI(1a) 启动和(1b)完成循证心理治疗(EBPsy)和循证心理治疗 药物疗法(循证医学)。2.可伸缩性：(2A)评估常用的QI和MTL保真度。(2B)测试MTL保真度 参与性措施的收敛效度。(2C)检验参与式变革理论：评估 12个月的EBP覆盖范围是否受团队参与性措施得分的影响。3.价格实惠： (3A)确定MTL的预算影响。(3B)。计算每增加1%的平均边际成本 EBP伸展。方法：我们提出了一项双臂、24个诊所(每臂12个)的整群随机试验来测试 MTL在扩大EBP触角方面优于常规QI。诊所将来自24个地区的医疗保健机构 系统(HCS)低于SAIL心理健康中值，与以下相关的8项SAIL测量中有3项处于较低水平 EBPS。计算机辅助分层区块随机化将在基线时平衡MTL和通常的QI臂 使用企业数据仓库(CDW)数据。参赛者为多学科前线团队。 瘾君子和心理健康提供者。后续步骤/实施：MTL是与合作伙伴共同开发的 与退伍军人事务部精神健康和自杀预防办公室(OMHSP)合作，如果被证明是有效的，可扩展的， 对于改善退伍军人及时获得EBP的经济实惠，MTL将在全国范围内扩展到更多的诊所，到 扩大MTL在线资源，并培训更多的VA人员，以促进MTL活动，而不是通常的QI。

Background: Evidence-based practices (EBPs) are the most high value treatments to meet Veterans’ addiction and mental health needs, reduce chronic impairment, and prevent suicide or overdose. Over 10 years, VA invested in dissemination of evidence-based psychotherapies and pharmacotherapies based on substantial evidence of effectiveness as compared to usual care. Quality metrics also track progress. Despite these investments, patients with prevalent needs, such as depression, PTSD and opioid use disorder often don’t receive EBPs. Systems theory explains limited EBP reach as a system behavior emerging dynamically from local components (e.g., patient demand/health service supply). Participatory research and engagement principles guide participatory system dynamics (PSD), a mixed-methods approach used in business and engineering, shown to be effective for improving quality with existing resources. Significance/Impact: We propose our study in the high priority area of VA addiction and mental health care to improve Veteran access to VA’s highest quality care. Our PSD program, Modeling to Learn (MTL), improves frontline management of dynamic complexity through simulations of staffing, scheduling and service referrals common in healthcare, across generalist and specialty programs, patient populations, and provider disciplines/treatments. Innovation: Recent synthesis of VA data in the enterprise-wide SQL Corporate Data Warehouse (CDW) makes it feasible to scale participatory simulation learning activities with VA frontline addiction and mental health staff. MTL is an advanced quality improvement (QI) infrastructure that helps VA take a major step toward becoming a learning health care system, by empowering local multidisciplinary staff to develop change strategies that fit to local capacities and constraints. Model parameters are from one VA source and generic across health services. If findings show that MTL is superior to usual VA quality improvement activities of data review with facilitators from VA program offices, this paradigm could prove useful across VA services. The PSD approach also advances implementation science. Systems theory explains how dynamic system behaviors (EBP reach) are defined by general scientific laws, yet arise from idiographic local conditions. Empowering staff with systems science simulation encourages the safe prototyping of ideas necessary for learning, increasing ongoing quality improvement capacities, and saving time and money as compared to trial-and-error approaches. Specific Aims: 1. Effectiveness: Test for superiority of MTL over usual QI for increasing the proportion of patients (1a) initiating, and (1b) completing a course of evidence-based psychotherapy (EBPsy) and evidence-based pharmacotherapy (EBPharm). 2. Scalable: (2a) Evaluate usual QI and MTL fidelity. (2b) Test MTL fidelity for convergent validity with participatory measures. (2c) Test the participatory theory of change: Evaluate whether 12 month period EBP reach is mediated by team scores on participatory measures. 3. Affordable: (3a) Determine the budget impact of MTL. (3b). Calculate the average marginal costs per 1% increase in EBP reach. Methodology: We propose a two-arm, 24-clinic (12 per arm) cluster randomized trial to test for superiority of MTL over usual QI for increasing EBP reach. Clinics will be from 24 regional health care systems (HCS) below the SAIL mental health median, and low on 3 of 8 SAIL measures associated with EBPs. Computer-assisted stratified block randomization will balance MTL and usual QI arms at baseline using Corporate Data Warehouse (CDW) data. Participants will be the multidisciplinary frontline teams of addiction and mental health providers. Next Steps/Implementation: MTL was developed in partnership with the VA Office of Mental Health and Suicide Prevention (OMHSP) and if shown to be effective, scalable, and affordable for improving timely Veteran access to EBPs, MTL will be scaled nationally to more clinics by expanding MTL online resources, and training more VA staff to facilitate MTL activities instead of usual QI.