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利用同伴和短信支持减少艾伯塔省急性精神病院出院患者的再入院率:一项创新支持计划的方案。

Reducing readmission rates for individuals discharged from acute psychiatric care in Alberta using peer and text message support: Protocol for an innovative supportive program.

机构信息

Department of Psychiatry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada.

Alberta Health Services, Addiction and Mental Health Services, Edmonton Zone, AB, Canada.

出版信息

BMC Health Serv Res. 2022 Mar 12;22(1):332. doi: 10.1186/s12913-022-07510-8.

DOI:10.1186/s12913-022-07510-8
PMID:35279142
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8917368/
Abstract

BACKGROUND

Individuals discharged from inpatient psychiatry units have the highest readmission rates of all hospitalized patients. These readmissions are often due to unmet need for mental health care compounded by limited human resources. Reducing the need for hospital admissions by providing alternative effective care will mitigate the strain on the healthcare system and for people with mental illnesses and their relatives. We propose implementation and evaluation of an innovative program which augments Mental Health Peer Support with an evidence-based supportive text messaging program developed using the principles of cognitive behavioral therapy.

METHODS

A pragmatic stepped-wedge cluster-randomized trial, where daily supportive text messages (Text4Support) and mental health peer support are the interventions, will be employed. We anticipate recruiting 10,000 participants at the point of their discharge from 9 acute care psychiatry sites and day hospitals across four cities in Alberta. The primary outcome measure will be the number of psychiatric readmissions within 30 days of discharge. We will also evaluate implementation outcomes such as reach, acceptability, fidelity, and sustainability. Our study will be guided by the Consolidated Framework for Implementation Research, and the Reach-Effectiveness-Adoption-Implementation-Maintenance framework. Data will be extracted from administrative data, surveys, and qualitative methods. Quantitative data will be analysed using machine learning. Qualitative interviews will be transcribed and analyzed thematically using both inductive and deductive approaches.

CONCLUSIONS

To our knowledge, this will be the first large-scale clinical trial to assess the impact of a daily supportive text message program with and without mental health peer support for individuals discharged from acute psychiatric care. We anticipate that the interventions will generate significant cost-savings by reducing readmissions, while improving access to quality community mental healthcare and reducing demand for acute care. It is envisaged that the results will shed light on the effectiveness, as well as contextual barriers and facilitators to implementation of automated supportive text message and mental health peer support interventions to reduce the psychological treatment and support gap for patients who have been discharged from acute psychiatric care.

TRIAL REGISTRATION

clinicaltrials.gov, NCT05133726 . Registered 24 November 2021.

摘要

背景

从住院精神病病房出院的患者再入院率是所有住院患者中最高的。这些再入院通常是由于精神卫生保健需求未得到满足,加上人力资源有限所致。通过提供替代的有效护理来减少住院需求,将减轻医疗保健系统的压力,同时也减轻精神疾病患者及其家属的压力。我们提出实施和评估一个创新项目,该项目通过使用认知行为疗法原则开发的基于证据的支持性短信程序,增强心理健康同伴支持。

方法

采用实用分步楔形聚类随机试验,每日支持性短信(Text4Support)和心理健康同伴支持为干预措施。我们预计将在阿尔伯塔省四个城市的 9 个急性精神病院和日间医院招募 10000 名患者,在他们出院时进行。主要结局指标为出院后 30 天内的精神科再入院人数。我们还将评估实施结果,如可及性、可接受性、忠实度和可持续性。我们的研究将由实施研究综合框架和实施-有效性-采用-维持框架指导。数据将从行政数据、调查和定性方法中提取。定量数据将使用机器学习进行分析。定性访谈将被转录,并使用归纳和演绎方法进行主题分析。

结论

据我们所知,这将是第一个评估急性精神病护理出院患者每日支持性短信程序与心理健康同伴支持相结合的影响的大型临床试验。我们预计,这些干预措施将通过减少再入院来节省大量成本,同时改善获得高质量社区精神卫生保健的机会,并减少对急性护理的需求。预计结果将揭示有效性,以及实施自动化支持性短信和心理健康同伴支持干预措施以减少急性精神病护理出院患者心理治疗和支持差距的背景障碍和促进因素。

试验注册

clinicaltrials.gov,NCT05133726。于 2021 年 11 月 24 日注册。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8917708/0215f54c0f0d/12913_2022_7510_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8917708/bdb945d4c173/12913_2022_7510_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8917708/0215f54c0f0d/12913_2022_7510_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8917708/bdb945d4c173/12913_2022_7510_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b497/8917708/0215f54c0f0d/12913_2022_7510_Fig2_HTML.jpg

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