Systems Analysis and Improvement Approach to Optimize the Task-Shared Mental Health Treatment Cascade (SAIA-MH): A ClusterRandomized Trial

优化任务共享心理健康治疗级联 (SAIA-MH) 的系统分析和改进方法：集群随机试验

• 批准号: 10208400
• 负责人: Bradley Wagenaar
• 金额: $ 66.45万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-10 至 2026-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10208400
• 关键词: Adherence; Advocate; Affect; Area; Attention; Caring; Climate; Clinical; Complex; Consolidated Framework for Implementation Research; Consultations; Data; Development; Diagnosis; Diagnostic; Drops; Effectiveness; Engineering; Equation; Facility Controls; Goals; HIV; Health; Health Personnel; Health Services Accessibility; Health system; Healthcare; Infant; Information Systems; Intervention; Knowledge; Learning; Link; Maintenance; Mental Health; Mental disorders; Modeling; Modification; Mother-to-child HIV transmission; Motion; Mozambique; Outcome; Outpatients; Pathway interactions; Patient-Focused Outcomes; Patients; Performance; Phase; Policies; Prevention; Procedures; Process; Provider; Psyche structure; Quality of Care; Reporting; Research Project Grants; Resources; Schizophrenia; Structure; Symptoms; System; Systems Analysis; Testing; Time; Treatment Step; Work; attentional control; budget impact; care systems; clinically significant; cost effectiveness; cost estimate; cost outcomes; design; disability; effective therapy; effectiveness testing; evidence base; follow-up; functional improvement; health care delivery; implementation determinants; implementation research; implementation strategy; improved; innovation; low and middle-income countries; markov model; medication compliance; microcosting; organizational structure; response; retention rate; scale up; success; tool

ABSTRACT Mental disorders are the leading cause of disability worldwide, yet treatment gaps exceed 90% in many low- and middle-income countries (LMICs). Significant progress is being made in access to mental healthcare through task-shifting to lower-level healthcare providers. However, while task-sharing may increase access to care, limited attention has been paid to assessing and optimizing quality of care across the mental health (MH) care cascade. An urgent need exists for evidence-based strategies to optimize the MH care cascade globally. Implementation strategies focused on one step in a care cascade can contribute to unintended system bottlenecks and quality of care issues. By contrast, the “Systems Analysis and Improvement Approach (SAIA)” is a multicomponent implementation strategy focused on optimizing quality across an entire care cascade. SAIA blends external/internal facilitation, enhanced local clinical consultation, and the creation of facility-level learning collaboratives with systems-engineering tools in a 5-step approach developed for task-shared providers. The 5 steps of SAIA include: (1) cascade analysis to visualize treatment cascade drop-offs and prioritize areas for system improvements; (2) process mapping to identify modifiable facility-level bottlenecks; (3) identification and implementation of modifications to improve system performance; (4) assessment of modification effects on the cascade; and (5) repeated analysis and improvement cycles. A previous trial established that the SAIA implementation strategy improved maternal ARV initiation and early infant diagnosis for the prevention of mother- to-child transmission HIV care cascade (R01HD075057; PI: Sherr). The SAIA implementation strategy has shown effectiveness for HIV cascade improvement, although no evidence exists on the effectiveness of SAIA applied to other complex treatment cascades – such as outpatient schizophrenia treatment. The present study aims to fill this knowledge gap by testing the following specific aims: Primary Aim 1: test the effectiveness of the SAIA-MH implementation strategy for schizophrenia cascade optimization using a cluster RCT and assess determinants of implementation success; Secondary Aim 1: test causal pathway models to analyze mechanisms of action for effects of the SAIA-MH implementation strategy; Aim 2: estimate the cost and cost-effectiveness of scaling-up SAIA-MH in Mozambique. In response to PAR-19-274, this project tests a multicomponent implementation strategy affecting “organizational structure, climate, culture, and processes”, with the goal to optimize the “implementation of diagnostic interventions, effective treatments, and clinical procedures into existing care”. This project also analyzes “mechanisms of action that explain the impact of a multi-component strategy to inform how these strategies can optimally be delivered across various settings”. If effective, the SAIA-MH implementation strategy has a large potential to be rapidly scaled-up to decrease gaps in task-shared MH treatments globally.

摘要 精神障碍是全世界导致残疾的主要原因，但在许多低收入和低收入人群中，治疗缺口超过90% 中等收入国家(LMIC)。在通过以下途径获得精神卫生保健方面正在取得重大进展 将任务转移到较低级别的医疗保健提供者。然而，虽然分担任务可能会增加获得护理的机会， 对评估和优化精神卫生(MH)护理的护理质量的关注有限 卡斯卡德。迫切需要以证据为基础的战略，以优化全球卫生保健级联。 专注于护理级联中的一个步骤的实施策略可能会导致意外的系统 瓶颈和护理质量问题。相比之下，“系统分析和改进方法(SAIA)” 是一种多组件实施战略，专注于优化整个护理级联的质量。赛亚 融合外部/内部促进、增强的本地临床咨询和创建设施级学习 与系统工程工具进行协作，采用为任务共享提供商开发的5步方法。5. SAIA的步骤包括：(1)级联分析，以可视化治疗级联下降并确定区域的优先顺序 系统改进；(2)过程映射，以确定可修改的设施级瓶颈；(3)确定和 实施修改以提高系统性能；(4)评估修改对 层叠；(5)重复分析和改进循环。先前的一次审判证明，SAIA 实施策略改进孕产妇抗逆转录病毒接种和婴儿早期诊断，预防母婴传播 儿童传播艾滋病毒护理级联(R01HD075057；PI：SHERR)。 SAIA实施战略已显示出对艾滋病毒连锁改善的有效性，尽管没有 有证据表明SAIA适用于其他复杂的级联治疗--例如门诊 精神分裂症治疗。本研究旨在通过测试以下具体目标来填补这一知识空白： 主要目标1：测试SAIA-MH精神分裂症连锁实施策略的有效性 使用分组RCT进行优化并评估实施成功的决定因素；次要目标1：测试 分析SAIA-MH实施战略效果作用机制的因果路径模型； 目标2：估计莫桑比克扩大SAIA-MH的成本和成本效益。 作为对PAR-19-274的响应，该项目测试了一种多组件实施战略，其影响 “组织结构、气候、文化和流程”，目标是优化“实施 将诊断性干预、有效治疗和临床程序纳入现有护理“。这个项目还 分析解释多组件战略的影响的行动机制，以告知这些 战略可以在各种环境中以最佳方式交付“。如果有效，SAIA-MH实施战略 有很大的潜力可以迅速扩大，以减少全球任务分担MH治疗方面的差距。