The Use of SMS Text Messaging to Improve the Hospital-to-Community Transition in Patients With Acute Coronary Syndrome (Txt2Prevent): Results From a Pilot Randomized Controlled Trial

Abstract

Background Acute coronary syndrome (ACS) is a leading cause of hospital admission in North America. Many patients with ACS experience challenges after discharge that impact their clinical outcomes and psychosocial well-being. SMS text messaging has the potential to provide support to patients during this postdischarge period. Objective This study pilot tested a 60-day SMS text messaging intervention (Txt2Prevent) for patients with ACS. The primary objective was to compare self-management domains between usual care and usual care plus Txt2Prevent. The secondary objectives were to compare medication adherence, health-related quality of life, self-efficacy, and health care resource use between groups. The third objective was to assess the feasibility of the study protocol and the acceptability of the intervention. Methods This was a randomized controlled trial with blinding of outcome assessors. We recruited 76 patients with ACS from St. Paul’s Hospital in Vancouver, Canada, and randomized them to 1 of 2 groups within 7 days of discharge. The Txt2Prevent program included automated 1-way SMS text messages about follow-up care, self-management, and healthy living. Data were collected during the index admission and at 60 days after randomization. The primary outcome was measured with the Health Education Impact Questionnaire (heiQ). Other outcomes included the EQ-5D-5L, EQ-5D-5L Visual Analog Scale, a modified Sullivan Cardiac Self-Efficacy Scale, and Morisky Medication Adherence Scale scores, and self-reported health care resource use. Analyses of covariance were used to test the effect of group assignment on follow-up scores (controlling for baseline) and were considered exploratory in nature. Feasibility was assessed with descriptive characteristics of the study protocol. Acceptability was assessed with 2 survey questions and semistructured interviews. Results There were no statistically significant differences between the groups for the heiQ domains (adjusted mean difference [Txt2Prevent minus usual care] for each domain—Health-directed activity: –0.13, 95% CI –0.39 to 0.13, P=.31; Positive and active engagement in life: 0.03, 95% CI –0.19 to 0.25, P=.76; Emotional distress: 0.04, 95% CI –0.22 to 0.29, P=.77; Self-monitoring and insight: –0.14, 95% CI –0.33 to 0.05, P=.15; Constructive attitudes and approaches: –0.10, 95% CI –0.36 to 0.17, P=.47; Skill technique and acquisition: 0.05, 95% CI –0.18 to 0.27, P=.69; Social integration and support: –0.12, 95% CI –0.34 to 0.10, P=.27; and Health services navigation: –0.05, 95% CI –0.29 to 0.19, P=.69). For the secondary outcomes, there were no statistically significant differences in adjusted analyses except in 1 self-efficacy domain (Total plus), where the Txt2Prevent group had lower scores (mean difference –0.36, 95% CI –0.66 to –0.50, P=.03). The study protocol was feasible, but recruitment took longer than expected. Over 90% (29/31 [94%]) of participants reported they were satisfied with the program. Conclusions The Txt2Prevent study was feasible to implement; however, although exploratory, there were no differences between the 2 groups in adjusted analyses except for 1 self-efficacy domain. As the intervention appeared acceptable, there is potential in using SMS text messages in this context. The design of the intervention may need to be reconsidered to have more impact on outcome measures. Trial Registration ClinicalTrials.gov NCT02336919; https://clinicaltrials.gov/ct2/show/NCT02336919 International Registered Report Identifier (IRRID) RR2-10.2196/resprot.6968

The effect of telemedicine on secondary prevention of atherosclerotic cardiovascular disease: A systematic review and meta-analysis

“…These studies were conducted in North America ( n = 5) ( 22 – 26 ), Europe ( n = 10) ( 14 , 27 – 35 ), Asia ( n = 9) ( 19 , 36 – 43 ), Africa ( n = 1) ( 44 ), Australia and New Zealand ( n = 6) ( 45 – 50 ), South America ( n = 1) ( 13 ). We included participants who were diagnosed with MI ( 24 , 29 , 32 , 34 , 35 , 37 , 44 , 47 ), ACS ( 14 , 22 , 31 , 33 , 49 ), CHD ( 13 , 19 , 23 , 27 , 28 , 30 , 40 , 41 , 45 , 46 , 48 , 50 ), Ischemic stroke ( 13 , 30 ) and PAD ( 13 , 19 , 30 ) or received coronary revascularization ( 13 , 19 , 23 , 25 , 26 , 28 , 29 , 33 , 36 , 38 , 39 , 42 , 43 , 45 , 48 , 49 ) in our review. The participants’ mean age varies from 55.8 to 70.36 and 20.04% of them are female.…”

“…Due to the existence of mixed intervention measures, we assume the main intervention measures as the measures of contact and interaction between researchers and patients. We classified the main intervention measures as telephone ( 14 , 26 , 28 , 33 , 35 , 37 , 39 , 47 , 48 ), e-mail and telephone ( 27 ), text message ( 22 , 24 , 31 , 36 , 49 , 50 ), mobile application ( 13 , 19 , 32 , 38 , 42 – 46 ), website ( 23 , 25 , 29 , 30 , 34 , 41 ) and website and mobile application ( 40 ).…”

“…We presented their main characteristics in Table 1. These studies were conducted in North America (n = 5) (22)(23)(24)(25)(26), Europe (n = 10) (14, [27][28][29][30][31][32][33][34][35], Asia (n = 9) (19,(36)(37)(38)(39)(40)(41)(42)(43), Africa (n = 1) (44), Australia and New Zealand (n = 6) (45-50), South America (n = 1) (13). We included participants who were diagnosed with…”

Evaluation of an Automated Text Message–Based Program to Reduce Use of Acute Health Care Resources After Hospital Discharge

“…22 Figure This study builds on a growing body of literature around the utility of automated hovering and text message-based strategies to support patients in the transition from hospital to home. [23][24][25][26][27][28] Prior studies have evaluated these approaches in a variety of clinical contexts, including after surgery and in specific disease states, such as heart failure. Of those studies that have evaluated the association with the use of acute care resources, the findings have been mixed, with some finding no significant difference, 23,24 and others similarly finding an associated reduction in readmissions.…”

“…30 High rates of satisfaction has been a consistent finding in other similar programs. 26,27 Last, our intervention was integrated into the preexisting workflow of the practice care management team, for whom responding to patient calls from recently discharged patients is part of their daily standard work. The intervention was integrated into these existing structures and generated a mean of 1.4 escalations per day, which the team considered a manageable workload.…”