Browsing by Author "Shalaby, Reham"

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    Reducing readmission rates for individuals discharged from acute psychiatric care in Alberta using peer and text message support: Protocol for an innovative supportive program
    (2022-03-12) 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 I. O.
    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