Reducing readmission rates for individuals discharged from acute psychiatric care in Alberta using peer and text message support: Protocol for an innovative supportive program
Authors: Eboreime Ejemai , Shalaby Reham , Mao Wanying , Owusu Ernest , Vuong Wesley , Surood Shireen , Bales Kerry , MacMaster Frank P. , McNeil Diane , Rittenbach Katherine , Ohinmaa Arto , Bremault-Phillips Suzette , Hilario Carla , Greiner Russ , Knox Michelle , Chafe Janet , Coulombe Jeff , Xin-Min Li , McLean Carla , Rathwell Rebecca , Snaterse Mark , Spurvey Pamela , Taylor Valerie H , McLean Susan , Urichuk Liana , Tzeggai Berhe , McCabe Christopher , Grauwiler David , Jordan Sara , Brown Ed , Fors Lindy , Savard Tyla , Grunau Mara , Kelton Frank , Stauffer Sheila , Cao Bo , Chue Pierre , Abba-Aji Adam , Silverstone Peter , Nwachukwu Izu , Greenshaw Andrew , Agyapong Vincent Israel Opoku 
Published: March 2022

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