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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?

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?
参与式系统动态与通常的质量改进:工作人员使用模拟是否是一种有效、可扩展且负担得起的方式来改善退伍军人及时获得高质量心理保健的机会?
批准号:
10247447
负责人:
Lindsey Eileen Zimmerman
金额:
$0.0万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-09-01 至 2025-09-30

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中文摘要
翻译
背景:循证医学实践(EBP)是满足退伍军人需求的最高价值的治疗方法。 成瘾和心理健康需求,减少慢性损伤,并防止自杀或过量。超过10 多年来,VA投资于传播基于证据的心理治疗和药物治疗, 与常规护理相比,有显著的有效性证据。质量指标也跟踪进度。 尽管有这些投资,但有普遍需求的患者,如抑郁症,创伤后应激障碍和阿片类药物使用, 通常不接受EBPs。系统理论将有限的EBP范围解释为系统行为 从本地组件动态出现(例如,病人需求/卫生服务供应)。参与性 研究和参与原则指导参与式系统动力学(PSD),一种混合方法 在商业和工程中使用的方法,被证明是有效的,以提高现有的质量 资源意义/影响:我们建议在VA成瘾和精神疾病的高优先领域进行研究。 医疗保健,以改善退伍军人获得VA的最高质量的护理。我们的PSD计划,建模学习 (MTL),通过模拟人员配备、调度, 和医疗保健中常见的服务转介,跨通才和专科项目,患者人群, 并提供纪律/治疗。创新:在企业范围的SQL中对VA数据的最新合成 企业数据仓库(CDW)使参与式模拟学习活动的规模化成为可能, 退伍军人管理局前线成瘾和心理健康工作人员。MTL是一种先进的质量改进(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, 多学科工作人员制定适合当地能力和制约因素的变革战略。模型 参数来自一个VA源,并且在卫生服务中是通用的。如果调查结果显示MTL是 上级于与VA项目办公室的促进者进行数据审查的常规VA质量改进活动, 该范例可以证明在VA服务中是有用的。私营部门司的办法还推动了执行工作 科学系统理论解释了动态系统行为(EBP范围)如何由一般 科学规律,但产生于具体的地方条件。通过系统科学仿真增强员工能力 鼓励对学习所需的想法进行安全的原型设计,增加持续的质量改进 与试错法相比,具体目标:1。 有效性:检验MTL相对于常规QI在增加患者比例方面的优效性(1a) 开始,和(1b)完成循证心理治疗(EBPsy)和循证心理治疗(EEPsy)课程。 药物治疗(EBPharm)。2.可扩展性:(2a)评估通常的QI和MTL保真度。(2b)测试MTL保真度 参与性测量的收敛效度。(2c)测试参与式变革理论:评估 是否12个月期间EBP达到由参与性措施的团队得分介导。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到达。方法:我们提出了一个两组,24个诊所(每组12个)的随机分组试验,以测试 MTL在增加EBP范围方面优于常规QI。诊所将来自24个区域卫生保健 系统(HCS)低于SAIL心理健康中位数,并且与SAIL相关的8个SAIL指标中有3个低 EBP。计算机辅助分层区组随机化将在基线时平衡MTL和常规QI组 使用企业数据仓库(CDW)数据。参加者将是多学科的前线队伍, 成瘾和心理健康提供者。后续步骤/实施:MTL是与合作伙伴共同开发的 与退伍军人事务部心理健康和自杀预防办公室(OMHSP)合作,如果证明是有效的,可扩展的, 和负担得起的改善退伍军人及时获得EBP,MTL将扩大到全国更多的诊所, 扩大MTL在线资源,培训更多的VA员工,以促进MTL活动,而不是通常的QI。
英文摘要
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.
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