Abstract
Background
Pediatric emergencies pose significant challenges in healthcare. Telemedicine offers a promising solution by enabling remote assessments, improving specialist access, reducing unnecessary ER visits and admissions, optimizing resources, and enhancing patient satisfaction. This systematic review and meta-analysis uniquely aimed to quantify the effect of telemedicine on key outcomes in pediatric emergency and post-emergency care.
Methods
We searched PubMed, Scopus, the Cochrane Library, and Web of Science to identify studies focusing on the impact of telemedicine in pediatric emergency settings. Both single- and double-arm studies were included. Statistical analysis was performed using RevMan and CMA software, with a random-effects model applied to all analyses. We assessed differences in admissions, hospital length of stay (LOS), and mortality. Event rates were calculated for single-arm analyses, and risk ratios and mean differences were used for dichotomous and continuous outcomes in double-arm analyses.
Results
A total of 23 studies were included. Telemedicine significantly reduced hospital LOS (MD = -1.01, 95% CI: -1.3 to -0.71) and overall mortality (RR = 0.17, 95% CI: 0.13 to 0.24). The admission rates to the emergency department, hospital ward, and pediatric intensive care unit (PICU) were comparable between both groups. Single-arm analysis revealed that telemedicine was associated with an ED admission rate of 18% (95% CI: 5.2–47%), a hospital ward admission rate of 16.7% (95% CI: 4.6–45.7%), and a pooled mortality rate of 1.8% (95% CI: 1–3.3%).
Conclusions
Telemedicine appears to be an effective tool in pediatric emergency care. While our analysis suggests reductions in hospital length of stay and mortality, these findings should be interpreted with caution due to variability and potential confounding across studies. The impact on admission rates remains inconclusive. Nonetheless, telemedicine offers a promising approach to enhancing healthcare delivery and optimizing resource use in pediatric emergency and early post-emergency settings.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12245-025-00968-3.
Keywords: Telemedicine, Pediatric, Emergency, Admission, Mortality, Meta-analysis
Background
Telemedicine generally refers to the use of digital communication to exchange medical information [1]. This may occur between a patient or caregiver and a doctor, or between healthcare providers, enabling remote diagnosis, expert consultation, patient monitoring, and treatment decisions. Telemedicine has emerged as a key solution to healthcare’s epidemiological, demographic, and economic challenges—especially recognized during the COVID-19 pandemic [2]. By allowing remote medical assessments, telemedicine can improve specialist access for rural and non-specialist providers, reduce unnecessary emergency department visits and hospital admissions, optimize resource use, and enhance patient satisfaction [1]. However, its implementation faces challenges such as technological barriers, limited awareness, gaps in digital literacy and language, and concerns about data security and privacy [3].
In emergency settings, where rapid diagnosis and intervention are critical, telemedicine has expanded healthcare access, minimized inequity, and enhanced the quality of emergency and acute care in remote areas [4]. Its effectiveness is well-documented in adult populations [5]. More recently, researchers have examined the use of telemedicine in pediatric emergencies, following positive feedback from physicians, children, and caregivers about its use in various clinical settings [6, 7]. Children are more vulnerable to emergent conditions, and the heightened sensitivity of their caregivers makes the role of telemedicine in pediatric emergency settings particularly important. Telemedicine can assist in triaging pediatric patients, accelerate hospital access when necessary, and reassure caregivers who may overestimate the severity of their child’s condition [8].
Previous reviews explored telemedicine in pediatric emergency care, focusing on different aspects like implementation challenges, clinical outcomes, cost outcomes, access, process measures [9, 10]. They concluded that telemedicine improves diagnostic accuracy, therapeutic decisions, and cost efficiency, with major benefits including shorter length of stay (LOS), better specialist access, direct cost savings, and higher patient satisfaction. To the best of our knowledge, this is the first meta-analysis to quantify the impact of telemedicine on pediatric emergency care, focusing on clinical outcomes such as admission rates, hospital length of stay, and mortality.
Methods
This study followed the PRISMA guidelines for systematic reviews and meta-analyses [11].
Search process
We searched PubMed, Scopus, the Cochrane Library, and the Web of Science (WOS) till February 2025. Details of search strategies and search results across the four databases are demonstrated in Table S1. Records were exported to EndNote for duplicate removal and subsequently screened by two independent reviewers based on titles and abstracts. Studies deemed relevant underwent a full-text review to determine eligibility according to our inclusion and exclusion criteria.
Eligibility criteria
We utilized the PICOS framework to select relevant studies: Population: children under 18 with emergency conditions; Intervention: telemedicine; Control: any comparator; Outcome: admission rates, mortality, and hospital length of stay. All primary study designs, including single- and double-arm studies, were eligible. For this review, we defined telemedicine as the use of real-time remote communication technologies—either video or telephone—to facilitate clinical decision-making or triage between a referring and a receiving provider. While video-based platforms constituted the majority of interventions, we included telephone consultations and triage services when they were the primary mode of remote communication, consistent with how the original studies described them under the umbrella of telemedicine. In studies where both video and telephone consultations were used, we classified them as telemedicine if either modality was employed to support clinical evaluation. Telephone-only groups were treated as control comparators when they were explicitly described as the prior standard of care or baseline condition before video-based telemedicine implementation. Studies were excluded if they lacked separate telemedicine data, did not report admission outcomes, or included both adult and pediatric populations without separately reported pediatric data.
Data extraction and risk of bias
Relevant data were extracted from the included studies by two independent reviewers. Study characteristics and baseline data, including age, gender, study design, location, patient numbers, population details, telemedicine and control details, primary outcomes, and common complaint categories, were extracted and tabulated. Data on emergency department (ED), ward, and pediatric intensive care unit (PICU) admissions, mortality, and hospital length of stay (LOS) were extracted and pooled for single- and double-arm analyses. Different quality assessment tools were used: the Risk of Bias 2 (ROB-2) tool for the two randomized controlled trials (RCTs), the Newcastle-Ottawa Scale (NOS) for the 19 observational studies, and the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) for the two diagnostic studies [12–14]. Discrepancies in screening and data extraction were resolved through discussion between the two reviewers. If consensus could not be reached, a third senior reviewer was consulted. In cases of missing data, we contacted study authors when possible. Where data remained unavailable, only reported outcomes were included in the analysis, and missing items were documented without imputation.
Statistical analysis
The analysis was conducted using RevMan version 5.4 for the double-arm analysis and Comprehensive Meta-Analysis (CMA) for the single-arm analysis. A random-effects model was adopted for all analyses to account for variability across studies. Statistical heterogeneity was quantified using the I² statistic, with values over 50% and a p-value below 0.1 indicating significant heterogeneity. As recommended in the Cochrane Handbook, meta-regression and publication bias were assessed when at least 10 studies were available for a given outcome [15]. Using a 95% confidence interval (CI), event rates were calculated for single-arm analyses. For double-arm analyses, risk ratios (RR) were used for dichotomous outcomes, and mean differences (MD) for continuous outcomes.
Results
Search results
A total of 2,925 records were identified after duplicate removal. A total of 228 studies were deemed relevant and underwent full-text screening. Finally, 23 studies were included [16–38]. The PRISMA flowchart is demonstrated in Fig. 1.
Fig. 1.
PRISMA flowchart outlining the systematic review process
Study characteristics and narrative synthesis
A total of 23 studies investigating telemedicine in pediatric emergencies were included. The studies comprised prospective, retrospective cohort studies, cross-sectional analyses, and randomized trials. Notably, the majority [14 out of 23] were conducted in the United States. Telemedicine interventions varied, including real-time video consultations, tablet-based communication, telephone triage services, smartphone applications, and tele-ED systems. Control groups typically consisted of patients receiving in-person care, standard emergency referrals, or telephone-only consultations. Summary and baseline data of the included studies are demonstrated in Tables S2, S3. The quality of RCTs and diagnostic studies was deemed low risk of bias (Figures S1, S2). Among the observational studies, 10 were of good quality, 8 were of poor quality, and 1 was of fair quality (Table S4-A&B).
Among the 23 included studies, two were excluded from the meta-analysis due to incompatible formats of outcome reporting [37, 38]. McConnochie et al. found that children with telemedicine access had 23% more overall healthcare visits but were 22% less likely to visit the ED, indicating potential cost savings by reducing unnecessary ED visits [38]. Mosquera et al., in a randomized controlled trial, showed that adding telemedicine to comprehensive care for medically complex children significantly reduced days of outside-home care, serious illnesses, and overall healthcare costs [37].
Meta-analysis
The single-arm analysis revealed that integrating telemedicine into pediatric emergency care was associated with a pooled hospital ward admission rate of 16.7% [95% CI: 4.6–45.7%] from 16 studies (Fig. 2), a pooled ER admission rate of 18% [95% CI: 5.2–47.1%] based on 11 studies (Fig. 3-A), and a pooled mortality rate of 1.8% [95% CI: 1–3.3%] derived from 5 studies (Fig. 3-B). Funnel plots are presented in Figures S3, S4, and S5. The analysis of ER admission and mortality showed no significant publication bias (p = 0.52) and (p = 0.57), respectively; however, hospital ward admission demonstrated significant publication bias (p = 0.002).
Fig. 2.
Forest plot of the pooled hospital ward admission rate among pediatric patients using telemedicine, based on 16 studies
Fig. 3.
Forest plots of single-arm analyses among pediatric telemedicine users: (A) Emergency department (ED) admission rate, based on 11 studies; (B) Mortality rate, based on 5 studies
The double-arm analysis comparing telemedicine users to non-users demonstrated inconsistent findings, with pooled results indicating no significant difference in ED admission rates between the groups [RR = 1.51, 95% CI: 0.41 to 5.5]. To explore the substantial heterogeneity (I² = 100%), we subgrouped the studies: three assessed ED admissions among patients who presented in person to healthcare providers, while the remaining two evaluated ED admissions following telemedicine home visits. However, substantial heterogeneity persisted across the studies (Fig. 4-A). Similarly, no significant difference was observed in the odds of hospital ward admissions [RR = 1.46, 95% CI: 0.71 to 3.00]; (I² = 99%) (Fig. 4-B). Consistently, no significant difference was observed regarding the Pediatric Risk of Admission Score 2 (PRISA-2) between both groups [MD = −0.06, 95% CI: −0.18 to 0.05]; (I² = 0%) (Figure S6).
Fig. 4.
Forest plots comparing pediatric outcomes between telemedicine and control groups: (A) Emergency department admissions (5 studies), (B) Hospital ward admissions (8 studies)
Meta-regression analysis was conducted to explore potential sources of heterogeneity in both outcomes—ER visits and hospital admissions—based on telemedicine modality (video consultation, voice-only, or virtual assessment), geographic location, and study design (prospective, retrospective, or cross-sectional). Unfortunately, none of the tested covariates significantly explained the between-study variance. Full results are available in Table S5.
No significant difference was observed in the odds of PICU admissions [RR = 1.12, 95% CI: 0.54 to 2.32]; (I² = 97%) (Fig. 5-A). Additionally, the Pediatric Risk of Mortality Score 3 (PRISM III), a severity-of-illness scoring system used in pediatric intensive care units (PICUs) to assess mortality risk in critically ill children, showed comparable scores between telemedicine and control groups [MD = −0.02, 95% CI: −1.85 to 1.81]; (I² = 75%) (Figure S7).
Fig. 5.
Forest plots comparing pediatric outcomes between telemedicine and control groups: (A) PICU admissions (5 studies), (B) Hospital length of stay (LOS) (3 studies), (C) Overall mortality (4 studies)
Telemedicine demonstrated significant advantages in reducing hospital length of stay (LOS) [MD = −1.01, 95% CI: −1.3 to −0.71]; (I² = 0%) (Fig. 5-B) and lowering the overall mortality rate [RR = 0.17, 95% CI: 0.13 to 0.24]. The heterogeneity in the mortality analysis was resolved using a leave-one-out test (I² = 0%) (Fig. 5-C).
Discussion
This meta-analysis synthesized current evidence on the use of telemedicine in pediatric emergency care. Overall, our findings suggest that telemedicine appears to be a safe intervention with potential benefits. Although our pooled analysis demonstrated statistically significant reductions in LOS and overall mortality among pediatric patients receiving telemedicine, these findings were largely driven by a single large study by Antony and colleagues, which contributed over 90% of the weight in both outcomes [35]. Although that study reported substantial improvements following the implementation of a digital referral network between district hospitals and a tertiary pediatric center, its pre-post design and long interval between cohorts introduce potential confounders that limit causal interpretation. Several other included studies did not find significant differences in LOS or mortality [22, 32, 34]. These variations likely reflect differences in study designs, settings, and telemedicine modalities. Notably, a previous meta-analysis of 10 trials across broader age groups and settings also found no significant differences between telemedicine and in-person care in terms of ED visits, admission, mortality, or patient satisfaction [39]. However, that review did not focus specifically on pediatric emergency settings. By narrowing our scope to children in acute care contexts, this study offers a more targeted perspective, though limited by the quality and heterogeneity of available data.
The single-arm meta-analysis revealed a pooled ER admission rate of 18.4%, hospital ward admission rate of 19.2%, and mortality rate of 1.7% among children evaluated via telemedicine. While these figures provide an overview of outcomes within telemedicine-supported pediatric emergency care, we acknowledge that, in isolation, they are difficult to interpret due to the absence of direct comparators or established population norms. The primary purpose of reporting these pooled estimates was descriptive: to characterize the clinical trajectory of pediatric patients managed through telemedicine and to offer reference values for future evaluations. However, their clinical significance remains uncertain without contextual benchmarks.
To better understand telemedicine’s clinical impact, we relied on the double-arm studies for comparative analyses. These showed conflicting results, with some reporting higher admission rates with telemedicine [20, 24] and others showing lower rates [26, 30, 38]. We believe that telemedicine has that bidirectional effect, escalating emergency care for severely emergent cases while sometimes reducing ED visits and subsequent hospital admissions for non-emergent cases. The predominance of one effect over the other depends on several factors. A key factor is the variation in clinical conditions and their severity. Additionally, hospitals implemented different triage models and telemedicine platforms, influencing clinical admission decisions. Studies using real-time video consultations tended to report lower admission rates, likely due to more accurate diagnoses and the ability to arrange remote follow-ups, thereby reducing the need for hospitalization [38]. In contrast, telephone-based triage systems often resulted in higher hospital referrals, possibly due to diagnostic uncertainties [16, 22]. Marcin and colleagues conducted a randomized crossover trial involving 696 acutely ill children. They found that those who received telemedicine consultations had a 7% lower risk of being transferred compared to those who were managed through phone consultations [22].
While telemedicine has demonstrated benefits in enhancing patient care, concerns persist regarding its accuracy and safety in the diagnosis and management of pediatric emergencies. Some studies have directly evaluated this issue. Esberk and colleagues assessed 210 pediatric burn patients via smartphone-based tele-evaluation. The agreement between telemedicine and in-person assessments was nearly perfect (Cohen’s kappa = 0.923), with extremely high consistency in estimating burn surface area (intraclass correlation = 0.999) [31]. Another study, by Haimi et al., assessed the accuracy of diagnoses and the appropriateness of decisions made during telemedicine interactions. It also compared these decisions with patient outcomes, such as parental compliance and follow-up visits. Results showed high diagnostic accuracy (98.5%) and decision reasonableness (92%), with low false-positive (2.65%) and false-negative (5.3%) rates, good sensitivity (82.85%), and high specificity (96.15%) [29]. In rural U.S. hospitals, Dharmar et al. found that live telemedicine consultations significantly reduced physician-related medication errors during emergency pediatric care [32]. These findings support specific integration strategies. For instance, tele-triage hubs staffed with pediatric specialists could be linked to rural or district emergency departments to support real-time decision-making, particularly in low-volume or low-resource settings. In urban hospitals during peak overcrowding or off-hours, telemedicine can serve as a “first screen” for low-acuity pediatric cases, improving flow without compromising safety. In low- and middle-income countries (LMICs), smartphone-based image or video transmission can enable remote evaluation of conditions like burns, trauma, and respiratory distress—reducing unnecessary referrals and optimizing scarce transport resources. Embedding telemedicine platforms into existing emergency workflows (e.g., triage algorithms, medication protocols, and follow-up scheduling systems) would enhance clinical decision support and continuity of care.
Strengths and limitations
Compared to previous reviews, this systematic review specifically focuses on the pediatric population in emergency settings, encompassing all forms of telemedicine with a broader inclusion of literature up to 2025. Additionally, we conducted a meta-analysis to quantitatively assess the pooled effectiveness of telemedicine. However, several limitations must be acknowledged. First, the included studies exhibited substantial heterogeneity, particularly in hospital admission and ER visit outcomes, which complicates the interpretation of pooled estimates. Although meta-regression analyses were conducted to explore potential sources of heterogeneity—including telemedicine modality (video, voice, or virtual assessment), geographic region, and study design (prospective, retrospective, or cross-sectional)—none of these covariates significantly accounted for the between-study variance. This suggests that additional unmeasured factors may underlie the observed variability. Second, the majority of included studies were observational, and only two were randomized controlled trials, which may introduce inherent biases and limit the strength of causal inferences. Notably, 8 of the 21 studies included in the meta-analysis were judged to be at high risk of bias, which limits the strength and generalizability of the pooled estimates. As such, the findings should be interpreted cautiously and regarded as preliminary. Nonetheless, this review helps identify critical gaps in current evidence and provides a quantitative baseline to inform future research. Third, variations in healthcare infrastructure and system organization across countries may influence telemedicine implementation and effectiveness, thereby limiting external validity. Most studies originated from high-income countries, with limited representation from low-resource settings such as Africa and the Middle East. Strengthening collaboration between well-established healthcare systems and resource-limited countries could enhance the effectiveness and adaptability of telemedicine. Furthermore, the development of a global repository of complex or rare pediatric cases would serve as a valuable educational tool, promote knowledge exchange, and support more effective telemedicine-based decision-making. Training healthcare personnel in remote case management and virtual triage protocols is equally essential to ensure safe and efficient care delivery in diverse settings.
Conclusion
Telemedicine appears to be a safe and potentially valuable tool in pediatric emergency care. While our meta-analysis suggests that telemedicine may be associated with reductions in hospital length of stay and mortality, these findings should be interpreted with caution, as they are heavily influenced by a single large observational study and may be subject to confounding. The effect of telemedicine on hospital and emergency department admission rates remains inconclusive due to substantial heterogeneity across studies. Despite these limitations, telemedicine holds promise for improving healthcare access and delivery, particularly in underserved or remote settings. Future research should prioritize high-quality, pediatric-focused studies and aim to standardize telemedicine protocols to optimize its effectiveness and ensure equitable, reliable emergency care.
Supplementary Information
Acknowledgements
The APC for this article was funded by Hamad Medical Corporation’s Medical Research Center (MRC).
Author contributions
A.N.A.: conceptualization, methodology, quality assessment, analysis, writing original draft, supervision. M.S.Z.: conceptualization, methodology, analysis, writing original draft. M.M.: data collection, quality assessment. S.M.: methodology, quality assessment. A.A.E.: data extraction, quality assessment. H.Y.M.: methodology, data collection, data extraction. All authors reviewed the manuscript and approved it for publication.
Funding
This research did not receive any grant from the public, commercial, or not-for-profit funding agencies.
Data availability
The data that support the findings of this study are available upon reasonable request.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
The article has been updated to correct the order of the figures.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Change history
10/20/2025
A Correction to this paper has been published: 10.1186/s12245-025-00996-z
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are available upon reasonable request.