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: 10403584
• 负责人: Bradley Wagenaar
• 金额: $ 59.73万
• 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/10403584
• 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; Infant; Information Systems; Intervention; Knowledge; Learning; Link; Maintenance; Mental Health; Mental Health Services; Mental disorders; Modeling; Modification; Mother-to-child HIV transmission; Motion; Mozambique; Outcome; Outpatients; Pathway interactions; Patient-Focused Outcomes; Patients; Performance; Persons; Phase; Policies; Prevention; Procedures; Process; Provider; Quality of Care; Reporting; Research Project Grants; Resource-limited setting; Schizophrenia; 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 精神障碍是全球残疾的主要原因，但在许多低收入和低收入国家， 中等收入国家（LMIC）。在获得精神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， 有限的注意力已经支付给评估和优化整个心理健康（MH）护理的护理质量 级联。迫切需要基于证据的战略，以优化全球MH护理级联。 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。系统分析和改进方法（SAIA） 是一个多方面的实施战略，重点是优化整个护理级联的质量。Saia 融合外部/内部促进，加强当地临床咨询，并创建设施级学习 与系统工程工具合作，采用为任务共享提供商开发的5步方法。的5 SAIA的步骤包括：（1）级联分析，以可视化治疗级联下降并优先考虑 系统改进;（2）流程映射，以确定可修改的设施级瓶颈;（3）识别和 实施改进以提高系统性能;（4）评估改进对 （5）反复分析和改进循环。此前的一项审判确定， 实施战略改善了孕产妇抗逆转录病毒治疗的启动和婴儿早期诊断，以预防母婴传播。 儿童传播HIV护理级联（R 01 HD 075057; PI：Sherr）。 SAIA执行战略显示出对艾滋病毒级联改善的有效性，尽管没有 有证据表明，SAIA适用于其他复杂的治疗级联，如门诊病人， 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： 主要目的1：测试SAIA-MH实施策略对精神分裂症级联反应的有效性 使用集群RCT进行优化，并评估实施成功的决定因素;次要目标1：测试 因果路径模型，分析SAIA-MH实施战略效果的作用机制; 目标2：估计在莫桑比克扩大SAIA-MH的成本和成本效益。 作为对PAR-19-274的回应，该项目测试了一个多组件实施策略， “组织结构、氛围、文化和流程”，目标是优化“实施 诊断干预、有效治疗和临床程序纳入现有护理”。该项目还 分析了“解释多成分战略影响的行动机制，以告知这些战略如何影响 可以在各种环境中最佳地实施战略”。如果有效，SAIA-MH执行战略 具有很大的潜力，可以迅速扩大规模，以减少全球任务共享MH治疗的差距。