Impact of Smartphone Apps on Reperfusion Times and Clinical Outcomes in Acute ST-Segment Elevation Myocardial Infarction: Systematic Review and Meta-Analysis

Abstract

Background: Smartphone- and tablet-based apps have been increasingly used in the management of acute ST-segment elevation myocardial infarction (STEMI), with the goal of enhancing care efficiency. These apps facilitate improved team coordination through a single platform, enabling secure sharing of clinical data, arrival times, and enabling data storage and processing capabilities. The potential of these technologies to reduce reperfusion times and improve both clinical and process outcomes, compared to traditional communication methods, is promising.

Objective: This study aimed to evaluate the effectiveness of smartphone-based interventions in reducing door-to-balloon (D2B) time, first medical contact-to-balloon (FMC2B) time, mortality, and false activation rates in STEMI care pathways.

Methods: This review followed the PRISMA guidelines and the PICO framework for eligibility criteria. Studies were included if they compared smartphone- or tablet-enabled interventions with usual care for STEMI management, focusing on D2B time, FMC2B time, short-term mortality, and false activation rates. A systematic literature search was conducted across MEDLINE, Embase, and Google Scholar for studies published between 2008 and 2024. Studies using purpose-built software or commercially available instant messaging apps that enabled digital ECG transfer and real-time communication between providers were included. The protocol was registered with PROSPERO (CRD42023481024). Data synthesis was performed using SPSS (IBM) with random-effects meta-analysis for continuous and binary outcomes.

Results: A total of 903 articles were identified after removing duplicates, and 21 studies, involving 3267 patients, were included. Studies varied in design: 14 being retrospective and 7 prospective, conducted across 12 countries. Thirteen studies evaluated dedicated apps, and 8 used instant messaging platforms such as WhatsApp (Meta Platforms Inc) and WeChat (Tencent Holdings Ltd). The primary outcome, D2B time, showed a significant reduction in the intervention group (mean difference -19.11 mins, 95% CI -26.22 to -12.00; P<.01), with substantial heterogeneity (I²=89%). A similar reduction in FMC2B time was observed (mean difference -19.85 minutes, 95% CI -29.45 to -20.25; P=.01). Subgroup analysis indicated a more pronounced reduction in D2B time in low-income countries compared to high-income countries. There were no significant differences regarding short-term mortality (risk difference -0.03, 95% CI -0.07 to 0.01; P=.10). False activation rates were evaluated in 7 studies, with varying results, but no pooled analysis was feasible due to differences in definitions and study design. The health care setting (ie, low- or high-income countries) was the most significant factor contributing to the observed heterogeneity in the meta-regression analysis.

Conclusions: Smartphone-based interventions significantly reduce reperfusion times in STEMI care pathways. Digital technology can improve the efficiency of STEMI management, particularly with lower-resource health care infrastructure. Future studies should explore the impact on long-term outcomes and investigate regional differences in treatment effects.

Keywords: ST-elevation myocardial infarction; STEMI; Telehealth; Telemedicine; applications; apps; cardiac; cardiologists; cardiology; digital; digital health; digital interventions; digital technology; door-to-balloon time; mHealth; mobile applications; mobile apps; mobile health; smartphones; tele-health; tele-medicine; virtual care; virtual health; virtual medicine.

Figure 1.. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) flowchart of articles identified during the search process.

Figure 2.. Forest plot from meta-analysis of unstandardized mean difference in door-to-balloon times (minutes) comparing telemedicine strategies versus usual care [15192022-252728303133undefinedundefinedundefined].

Figure 3.. Forest plot from meta-analysis of unstandardized mean difference in first medical contact-to-balloon times (minutes) comparing telemedicine strategies versus usual care [91121222528-3032undefinedundefined].

Figure 4.. Forest plot from meta-analysis of risk difference in in- hospital or 30-day mortality comparing telemedicine strategies versus usual care [111923-253033undefinedundefined].