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

Postdischarge needs identified by an automated text messaging program: A mixed-methods study

BACKGROUND

Text messaging has emerged as a popular strategy to engage patients after hospital discharge. Little is known about how patients use these programs and what types of needs are addressed through this approach.

OBJECTIVE

The goal of this study was to describe the types and timing of postdischarge needs identified during a 30-day automated texting program.

METHODS

The program ran from January to August 2021 at a primary care practice in Philadelphia. In this mixed-methods study, two reviewers conducted a directed content analysis of patient needs expressed during the program, categorizing them along a well-known transitional care framework. We describe the frequency of need categories and their timing relative to discharge.

RESULTS

A total of 405 individuals were enrolled; the mean (SD) age was 62.7 (16.2); 64.2% were female; 47.4% were Black; and 49.9% had Medicare insurance. Of this population, 178 (44.0%) expressed at least one need during the 30-day program. The most frequent needs addressed were related to symptoms (26.8%), coordinating follow-up care (20.4%), and medication issues (15.7%). The mean (SD) number of days from discharge to need was 10.8 (7.9); there were no significant differences in timing based on need category.

CONCLUSIONS

The needs identified via an automated texting program were concentrated in three areas relevant to primary care practice and within nursing scope of practice. This program can serve as a model for health systems looking to support transitions through an operationally efficient approach, and the findings of this analysis can inform future iterations of this type of program.

Mobile phone text messaging for medication adherence in secondary prevention of cardiovascular disease

BACKGROUND

Cardiovascular diseases (CVDs) are the leading cause of death globally, accounting for almost 18 million deaths annually. People with CVDs have a five times greater chance of suffering a recurrent cardiovascular event than people without known CVDs. Although drug interventions have been shown to be cost-effective in reducing the risk of recurrent cardiovascular events, adherence to medication remains suboptimal. As a scalable and cost-effective approach, mobile phone text messaging presents an opportunity to convey health information, deliver electronic reminders, and encourage behaviour change. However, it is uncertain whether text messaging can improve medication adherence and clinical outcomes. This is an update of a Cochrane review published in 2017.

OBJECTIVES

To evaluate the benefits and harms of mobile phone text messaging for improving medication adherence in people with CVDs compared to usual care.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, four other databases, and two trial registers. We also checked the reference lists of all primary included studies and relevant systematic reviews and meta-analyses. The date of the latest search was 30 August 2023.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) with participants with established arterial occlusive events. We included trials investigating interventions using short message service (SMS) or multimedia messaging service (MMS) with the aim of improving adherence to medication for the secondary prevention of cardiovascular events. The comparator was usual care. We excluded cluster-RCTs and quasi-RCTs.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our primary outcomes were medication adherence, fatal cardiovascular events, non-fatal cardiovascular events, and combined CVD event. Secondary outcomes were low-density lipoprotein cholesterol for the effect of statins, blood pressure for antihypertensive drugs, heart rate for the effect of beta-blockers, urinary 11-dehydrothromboxane B2 for the antiplatelet effects of aspirin, adverse effects, and patient-reported experience. We used GRADE to assess the certainty of the evidence for each outcome.

MAIN RESULTS

We included 18 RCTs involving a total of 8136 participants with CVDs. We identified 11 new studies in the review update and seven studies in the previous version of the review. Participants had various CVDs including acute coronary syndrome, coronary heart disease, stroke, myocardial infarction, and angina. All studies were conducted in middle- and high-income countries, with no studies conducted in low-income countries. The mean age of participants was 53 to 64 years. Participants were recruited from hospitals or cardiac rehabilitation facilities. Follow-up ranged from one to 12 months. There was variation in the characteristics of text messages amongst studies (e.g. delivery method, frequency, theoretical grounding, content used, personalisation, and directionality). The content of text messages varied across studies, but generally included medication reminders and healthy lifestyle information such as diet, physical activity, and weight loss. Text messages offered advice, motivation, social support, and health education to promote behaviour changes and regular medication-taking. We assessed risk of bias for all studies as high, as all studies had at least one domain at unclear or high risk of bias. Medication adherence Due to different evaluation score systems and inconsistent definitions applied for the measurement of medication adherence, we did not conduct meta-analysis for medication adherence. Ten out of 18 studies showed a beneficial effect of mobile phone text messaging for medication adherence compared to usual care, whereas the other eight studies showed either a reduction or no difference in medication adherence with text messaging compared to usual care. Overall, the evidence is very uncertain about the effects of mobile phone text messaging for medication adherence when compared to usual care. Fatal cardiovascular events Text messaging may have little to no effect on fatal cardiovascular events compared to usual care (odds ratio 0.83, 95% confidence interval (CI) 0.47 to 1.45; 4 studies, 1654 participants; low-certainty evidence). Non-fatal cardiovascular events We found very low-certainty evidence that text messaging may have little to no effect on non-fatal cardiovascular events. Two studies reported non-fatal cardiovascular events, neither of which found evidence of a difference between groups. Combined CVD events We found very low-certainty evidence that text messaging may have little to no effect on combined CVD events. Only one study reported combined CVD events, and did not find evidence of a difference between groups. Low-density lipoprotein cholesterol Text messaging may have little to no effect on low-density lipoprotein cholesterol compared to usual care (mean difference (MD) -1.79 mg/dL, 95% CI -4.71 to 1.12; 8 studies, 4983 participants; very low-certainty evidence). Blood pressure Text messaging may have little to no effect on systolic blood pressure (MD -0.93 mmHg, 95% CI -3.55 to 1.69; 8 studies, 5173 participants; very low-certainty evidence) and diastolic blood pressure (MD -1.00 mmHg, 95% CI -2.49 to 0.50; 5 studies, 3137 participants; very low-certainty evidence) when compared to usual care. Heart rate Text messaging may have little to no effect on heart rate compared to usual care (MD -0.46 beats per minute, 95% CI -1.74 to 0.82; 4 studies, 2946 participants; very low-certainty evidence).

AUTHORS' CONCLUSIONS

Due to limited evidence, we are uncertain if text messaging reduces medication adherence, fatal and non-fatal cardiovascular events, and combined cardiovascular events in people with cardiovascular diseases when compared to usual care. Furthermore, text messaging may result in little or no effect on low-density lipoprotein cholesterol, blood pressure, and heart rate compared to usual care. The included studies were of low methodological quality, and no studies assessed the effects of text messaging in low-income countries or beyond the 12-month follow-up. Long-term and high-quality randomised trials are needed, particularly in low-income countries.

Investigating patient engagement associations between a postdischarge texting programme and patient experience, readmission and revisit rates outcomes

OBJECTIVES

This study aimed (1) to examine the association between patient engagement with a bidirectional, semiautomated postdischarge texting programme and Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey outcomes, readmissions and revisit rates in a large health system and (2) to describe operational and clinical flow considerations for implementing a postdischarge texting programme.

SETTING

The study involved 1 main academic hospital (beds: 2500+) and 6 community hospitals (beds: 190-400, averaging 300 beds per hospital) in Houston, Texas.

METHODS

Retrospective, observational cohort study between non-engaged patients (responded with 0-2 incoming text messages) and engaged patients (responded with 3+ incoming, patient-initiated text messages) between December 2022 and May 2023. We used the two-tailed t-test for continuous variables and χ2 test for categorical variables to compare the baseline characteristics between the two cohorts. For the binary outcomes, such as the revisit (1=yes, vs 0=no) and readmissions (1=yes vs 0=no), we constructed mixed effect logistic regression models with the random effects to account for repeated measurements from the hospitals. For the continuous outcome, such as the case mix index (CMI), a generalised linear quantile mixed effect model was built. All tests for significance were two tailed, using an alpha level of 0.05, and 95% CIs were provided. Significance tests were performed to evaluate the CMI and readmissions and revisit rates.

RESULTS

From 78 883 patients who were contacted over the course of this pilot implementation, 49 222 (62.4%) responded, with 39 442 (50%) responded with 3+ incoming text messages. The engaged cohort had higher HCAHPS scores in all domains compared with the non-engaged cohort. The engaged cohort used significantly fewer 30-day acute care resources, experiencing 29% fewer overall readmissions and 20% fewer revisit rates (23% less likely to revisit) and were 27% less likely to be readmitted. The results were statistically significant for all but two hospitals.

CONCLUSIONS

This study builds on the few postdischarge texting studies, and also builds on the patient engagement literature, finding that patient engagement with postdischarge texting can be associated with fewer acute care resources. To our knowledge, this is the only study that documented an association between a text-based postdischarge programme and HCAHPS scores, perhaps owing to the bidirectionality and ease with which patients could interact with nurses. Future research should explore the texting paradigms to evaluate their associated outcomes in a variety of postdischarge applications.

Impact of mHealth application on adherence to cardiac rehabilitation guidelines after a coronary event: Randomised controlled clinical trial protocol

Background

Coronary disease is the main cause of death around the world. mHealth technology is considered attractive and promising to promote behavioural changes aimed at healthy lifestyle habits among coronary patients. The purpose of this study is to evaluate the efficacy of an mHealth intervention regarding improved results in secondary prevention in patients after an acute myocardial infarction (AMI) or angina in terms of lifestyle, clinical variables and therapeutic compliance.

Methods

Randomised clinical trial with 300 patients who underwent a percutaneous coronary intervention (PCI) with stent implant. They will be assigned to either the mHealth group, subject to a self-monitored educational intervention involving an internet application installed on their mobile phone or tablet, or to a control group receiving standard healthcare (150 patients in each arm). The primary outcome variables will be adherence to the Mediterranean diet, physical activity, smoking, therapeutic compliance, knowledge acquired, user-friendliness and satisfaction with the application. Measurements of blood pressure, heart rate, body weight, waist circumference (WC) and the 6-min walk test will be taken. Furthermore, the blood lipid profile, glucose and HbA1c will be evaluated. Clinical interview will be conducted, and validated questionnaires completed. The primary quantitative results will be compared using an analysis of covariance adjusted for age and sex. A multivariate analysis will be performed to examine the association of the intervention with lifestyle habits, the control of cardiovascular risk factors (CDRFs) and the results after the hospital discharge (major adverse events, treatment compliance and lifestyle).

Conclusions

The study will provide evidence about the effectiveness of an mHealth intervention at improving the lifestyle of the participants and could be offered to patients with coronary disease to complement existing services.

Trial registration

NCT05247606. [https://ClinicalTrials.gov]. 21/02/2022.

Digital Health Interventions in Patient Management Following Acute Coronary Syndrome: A Meta-Analysis of the Literature

OBJECTIVE

Acute coronary syndrome patients should be closely followed-up to maintain optimal adherence to medical treatments and to reduce adverse events. Digital health interventions might provide improved outcomes for patient care by providing closer follow- up, compared to standard care. Thus, in this meta-analysis, we aimed to evaluate the effect of digital health interventions on follow-up in acute coronary syndrome patients.

METHODS

We searched medical databases to obtain all relevant studies comparing digital health interventions with standard care in acute coronary syndrome patients. After reviewing all eligible studies, a meta-analysis was conducted with the remaining 11 randomized controlled studies and 2 non-randomized controlled studies. A modified Jadad scale and Newcastle-Ottawa scale were used to assess the quality of the publications for randomized controlled studies and non-randomized controlled studies, respectively.

RESULTS

This meta-analysis consisted of 7657 patients. The all-cause mortality rate was 49% lower in the digital health intervention cases, compared to those who received standard care [relative risk (RR) = 0.51 (0.37; 0.70), P <.01]. There was a significant decrease in systolic blood pressure in the digital health interventions group, compared to the standard care group [mean difference = -5.28 (-9.47; -1.08), P =.01]. The rate of nonadherence to anti-aggregant drugs was 69% lower in the digital health interventions than in the standard care group [RR = 0.31 (0.20; 0.46), P <.01]. Also, nonadherence rates for statin and beta-blockers were lower in the digital health interventions group. The risk of rehospitalization was observed to be 55% less in the digital health interventions patients, compared to the standard care group [RR = 0.45 (0.30; 0.67), P <.01].

CONCLUSION

Digital health interventions can be effective in follow-up for secondary prevention in acute coronary syndrome patients.

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

Aim

The purpose of this systematic review was to evaluate the efficiency of telemedicine on the secondary level of prevention of patients with arteriosclerotic cardiovascular disease (ASCVD), provide evidence for the application of telemedicine in secondary prevention and promote the development of telemedicine in secondary prevention.

Methods

A computer-based search was conducted in MEDLINE, Embase, Pubmed, EBSCO, CINAHL, the Cochrane Library, and Web of Science. Randomized controlled trials regarding the effect of telemedicine on secondary prevention of ASCVD were included from inception to May, 2022. Meta-analysis was used to compare the results of the included studies by RevMan5.4 software. The Cochrane Collaboration bias risk tool was used to perform risk of bias assessment in this study. Outcomes included risk factors, physical activity and exercise, muscle function, exercise compliance, medication adherence, healthy diet, depression and anxiety, self-efficacy, knowledge score, economy, and safety endpoints. Subgroup analysis was carried out for different main intervention measures included in the literature.

Results

A total of 32 randomized clinical studies (n = 10 997 participants) were included in the meta-analysis. Compared with usual secondary prevention (USP) group, participants in telemedicine of secondary prevention (TOSP) group showed significant improvement in some risk factors including BMI (MD -0.87, p = 0.002), SBP (MD -4.09, p = 0.007) and DBP (MD -2.91, p = 0.0002) when they use the telephone as the intervention. In physical activity and exercise, Patients in TOSP showed an improvement in VO2 Peak (mL⋅kg-1⋅min-1) (OR 1.58, p = 0.02), 6MWT (MD 21.41, p = 0.001), GSLTPA score (MD 2.89, p = 0.005). Effects on medication adherence, exercise compliance, muscle function, healthy diet, economy and self-efficacy were synthesized narratively. Patients in TOSP did not show a reduction in knowledge score, depression, anxiety and safety endpoints.

Conclusion

There is a net benefit of secondary prevention supported by telemedicine (especially when using the telephone as an intervention) in patients with ASCVD in the terms of some risk factors, physical activity and exercise. There are still controversies in the improvement of medication adherence, exercise compliance, muscle function, healthy diet, knowledge score, self-efficacy and economy via telemedicine, which is worth exploring. Larger samples size and longer-term follow-ups are needed in future studies.

Systematic review registration

[https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=330478], identifier [CRD42022330478].

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

IMPORTANCE

Posthospital contact with a primary care team is an established pillar of safe transitions. The prevailing model of telephone outreach is usually limited in scope and operationally burdensome.

OBJECTIVE

To determine whether a 30-day automated texting program to support primary care patients after hospital discharge is associated with reductions in the use of acute care resources.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used a difference-in-differences approach at 2 academic primary care practices in Philadelphia from January 27 through August 27, 2021. Established patients of the study practices who were 18 years or older, were discharged from an acute care hospitalization, and received the usual transitional care management telephone call were eligible for the study. At the intervention practice, 604 discharges were eligible and 430 (374 patients, of whom 46 had >1 discharge) were enrolled in the intervention. At the control practice, 953 patients met eligibility criteria. The study period, including before and after the intervention, ran from August 27, 2020, through August 27, 2021.

EXPOSURE

Patients received automated check-in text messages from their primary care practice on a tapering schedule during the 30 days after discharge. Any needs identified by the automated messaging platform were escalated to practice staff for follow-up via an electronic medical record inbox.

MAIN OUTCOMES AND MEASURES

The primary study outcome was any emergency department (ED) visit or readmission within 30 days of discharge. Secondary outcomes included any ED visit or any readmission within 30 days, analyzed separately, and 30- and 60-day mortality. Analyses were based on intention to treat.

RESULTS

A total of 1885 patients (mean [SD] age, 63.2 [17.3] years; 1101 women [58.4%]) representing 2617 discharges (447 before and 604 after the intervention at the intervention practice; 613 before and 953 after the intervention at the control practice) were included in the analysis. The adjusted odds ratio (aOR) for any use of acute care resources after implementation of the intervention was 0.59 (95% CI, 0.38-0.92). The aOR for an ED visit was 0.77 (95% CI, 0.45-1.30) and for a readmission was 0.45 (95% CI, 0.23-0.86). The aORs for death within 30 and 60 days of discharge at the intervention practice were 0.92 (95% CI, 0.23-3.61) and 0.63 (95% CI, 0.21-1.85), respectively.

CONCLUSIONS AND RELEVANCE

The findings of this cohort study suggest that an automated texting program to support primary care patients after hospital discharge was associated with significant reductions in use of acute care resources. This patient-centered approach may serve as a model for improving postdischarge care.