Executive summary of ReCAPS
Background: Stroke imposes a large burden of suffering on survivors, with ongoing risk of recurrent stroke, depression and poor quality of life post discharge. In the era of technology being widely available and used by the majority of the population, low cost, scalable electronic support to increase self-efficacy with professional input for goal setting may improve the transition to home, and reduce hospital readmissions.
Aims/Methods: This Phase III prospective, parallel two group, double blind, multi-site, individual-randomised controlled trial will test the potential effectiveness of a comprehensive electronic self-management support program provided for 12 weeks after hospital discharge on emergency department presentations or hospital readmissions and to improve patient self-efficacy. The discharge support program comprises:
- a discharge care planning pack with standardised Recovery Goal Setting for use by clinicians and patients; and
- technology-based tools with integrated SMS/email messaging gateway permitting personalised and tailored messages based on patient nominated goals (iVERVE).
We aim to recruit 890, with potential adaptive sample size re-estimation up to a maximum of 1100 patients discharged home within 10 days of their stroke admission. Baseline assessments will be completed by hospital clinicians who, using the ReCAPS structured goal setting menu, will assist participants to identify 2 to 5 health and recovery goals they wish to achieve within a 12-week timeframe. Participants will be contacted by a Monash university researcher 7-14 days after hospital discharge. During this phone interview, the researcher assists in structuring the stated goals into measurable goals using the SMART criteria. Participants are then randomised to receive either treatment or control interventions. The researcher will schedule electronic messages to be sent over a period of 12 weeks via email or SMS, in accordance with the participant’s preference and their group allocation. Around 90 days and 12 months post-randomisation, outcome measures will be collected over the phone, or by postal survey, by an assessor blinded to the participants’ group allocation.
Statistical analysis: Primary analyses will be based on intention-to-treat. Descriptive statistics (e.g. Chi-square test) will be used to compare presentations/readmissions to hospital within 3 months post discharge for each intervention group. Random effects multi-level logistic regression models will be used with presentations/readmissions to hospitals (dichotomised as Yes/No) as the dependent variable, intervention groups as the independent variable and the level hospital. The potential for heterogeneity of treatment effects across centres will be examined using appropriate random effects regression models (with centre as the random effect). For secondary outcomes, generalised linear regression models will be used with the follow-up outcomes as the dependent variable, intervention groups as the independent variable and the baseline outcome will serve as the covariate.