Objectives: Patients discharged from the emergency department (ED) are often referred for primary care, specialty, or other disease-specific follow-up appointments. Attendance at these scheduled follow-up appointments has been found to improve patient outcomes, decrease ED bounce-backs, and reduce malpractice risk. Reasons for missing follow-up visits are complex, but the most commonly reason cited by patients is simply forgetting. In this study the authors evaluated the ability of an automated text message reminder system to increase attendance at post-ED discharge follow-up appointments in a predominantly Hispanic safety-net population.
Methods: This was a randomized controlled trial of ED patients with outpatient follow-up visits scheduled at the time of ED discharge. A total of 374 English- and Spanish-speaking patients with text-capable mobile phones were enrolled. Patients in the intervention arm received automated, personalized text message appointment reminders including date, time, and clinic location at 7, 3, and 1 day before scheduled visits. A t-test of proportions was used to compare outcomes between intervention and control groups. Both an intention-to-treat (ITT) and a per-protocol analysis of the data were performed. The ITT more accurately reflects real-world conditions where errors such as number entry errors are bound to occur. The per-protocol analysis adds value by isolating the effect of the intervention by comparing patients who actually received it compared with those who did not.
Results: In the per-protocol analysis of the primary outcome, the overall appointment adherence rate was 72.6% in the intervention group compared with 62.1% in the control group (difference between groups = 10.5%, 95% confidence interval [CI] = 0.3% to 20.8%; p = 0.045; number needed to treat = 9.5). In the ITT analysis, the overall appointment attendance rate 70.2% in the intervention group compared with 62.1% in the control group (difference between groups = 8.2%; 95% CI = -1.6% to 17.7%; p = 0.100). In a secondary largely exploratory analysis, the intervention was found to have the most benefit in patients with the lowest baseline follow-up rate (English speakers with specialty care appointments).
Conclusions: Automated text message appointment reminders resulted in improvement in attendance at scheduled post-ED discharge outpatient follow-up visits and represent a low-cost and highly scalable solution to increase attendance at post-ED follow-up appointments, which should be further explored in larger sample sizes and diverse patient populations.
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http://dx.doi.org/10.1111/acem.12503 | DOI Listing |
Data Brief
December 2024
Department of Computer Engineering, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
With the development of smart buildings, the risks of cyber-attacks against them have also increased. One of the popular and evolving protocols used for communication between devices in smart buildings, especially HVAC systems, is the BACnet protocol. Machine learning algorithms and neural networks require datasets of normal traffic and real attacks to develop intrusion detection (IDS) and prevention (IPS) systems that can detect anomalies and prevent attacks.
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December 2024
Institute for Human Development, Aga Khan University, Nairobi, Kenya.
Background: Engaging fathers(to-be) can improve maternal, newborn, and child health outcomes. However, father-focused interventions in low-resource settings are under-researched. As part of an integrated early childhood development pilot cluster randomised trial in Nairobi's informal settlements, this study aimed to test the feasibility of a text-only intervention for fathers (SMS4baba) adapted from one developed in Australia (SMS4dads).
View Article and Find Full Text PDFChest
December 2024
Department of Medicine, Division of Pulmonary and Critical Care Medicine, University of Rochester Medical Center, Rochester, New York. Electronic address:
J Subst Use Addict Treat
December 2024
College of Social Work, University of Kentucky, United States of America.
Background: Two scientific and clinical challenges for treating cannabis use disorder (CUD) are developing efficacious treatments with high likelihood of uptake and scalability, and testing the clinical mechanisms by which treatments work. Because young adults experience more CUD than other age groups, a need exists to test the efficacy and hypothesized causal pathways of novel treatments for CUD. Text-delivered treatments have the potential to reach young adults by increasing access and perceived privacy.
View Article and Find Full Text PDFFront Psychol
December 2024
Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Cluj-Napoca, Romania.
Background: Digital interventions present potential solutions for aftercare and relapse prevention in anxiety and depressive disorders. This systematic review synthesizes evidence on the efficacy of internet- and mobile-based interventions for post-acute care in these conditions.
Methods: A systematic search was conducted in electronic databases (MEDLINE, CENTRAL, Scopus, Web of Science, PsycINFO, PsycARTICLES, PsycEXTRA, ProQuest Dissertations and Theses Open, Open Access Theses and Dissertations, and Open Grey) for randomized controlled trials evaluating digital aftercare or relapse prevention interventions for adults with anxiety or depressive disorders.
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