Objectives: To evaluate the impact of synchronous telemedicine models on the clinical outcomes in pediatric acute care settings.
Data Sources: Citations from EBM Reviews, MEDLINE, EMBASE, Global Health, PubMed, and CINAHL.
Study Selection: We identified studies that evaluated the impact of synchronous telemedicine on clinical outcomes between January 2000 and April 2018. All studies involving acutely ill children in PICUs, pediatric cardiac ICUs, neonatal ICUs, and pediatric emergency departments were included. Publication inclusion criteria were study design, participants characteristics, technology type, interventions, settings, outcome measures, and languages.
Data Extraction: Two authors independently screened each article for inclusion and extracted information, including telecommunication method, intervention characteristics, sample characteristics and size, outcomes, and settings.
Data Synthesis: Out of the 789 studies initially identified, 24 were included. The six main outcomes of interest published were quality of care, hospital and standardized mortality rate, transfer rate, complications and illness severity, change in medical management, and length of stay. The use of synchronous telemedicine results improved quality of care and resulted in a decrease in the transfer rate (31-87.5%) (four studies), a shorter length of stay (8.2 vs 15.1 d) (six studies), a change or reinforcement of the medical care plan, a reduction in complications and illness severity, and a low hospital and standardized mortality rate. Overall, the quality of the included studies was weak.
Conclusions: Despite the broad recommendations found for using telemedicine in pediatric acute care settings, high-quality evidence of its impacts is still lacking. Further robust studies are needed to better determine the clinical effectiveness and the associated impacts of telemedicine in pediatric acute care settings.
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http://dx.doi.org/10.1097/PCC.0000000000001733 | DOI Listing |
BMJ Glob Health
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Departament of Internal Medicine, Medical School, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil.
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College of Nursing, Yonsei University, Seoul, Republic of Korea.
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Department of Family Medicine, Faculty of Medicine, McGill University, 5858 Ch. de la Côte des Neiges, Montreal, QC, H3S 1Z1, Canada.
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Department of Health and Exercise Science, Colorado State University, Fort Collins, CO, United States.
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Int J Med Inform
January 2025
Artificial Intelligence in Medical Sciences Research Center , Smart University of Medical Sciences, Tehran, Iran; Department of Artificial Intelligence, Smart University of Medical Sciences, Tehran, Iran. Electronic address:
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