Survey to evaluate clinical benefits and acceptance in international tele-intensive care unit collaboration
Clinical Snapshot
PICO Framework
| P — Population | Clinical staff (n=30) at ten spoke sites in four countries connected to one tele-intensive care unit hub |
| I — Intervention | International tele-intensive care unit (TICU) collaboration and support |
| C — Comparator | Not applicable (descriptive survey study) |
| O — Outcomes | Subjective clinical benefit, acceptance, trust, working relationships, and perceptions of ethical/data protection issues in telemedicine |
Bottom Line
This international survey of 30 clinical staff across ten tele-ICU spoke sites found generally positive perceptions of remote critical care support, with participants reporting good clinical and personal support, high acceptance, and trust in the telemedicine collaboration. The study highlights the importance of ethical principles and data protection in international telemedicine networks. However, the research is limited by its small sample size, lack of methodological detail, and absence of objective outcome measures. While the findings suggest potential for international tele-critical care expansion, the study provides insufficient evidence to guide implementation decisions. Larger, more rigorous evaluations with mixed-methods approaches and objective clinical outcomes are needed to establish the true effectiveness and optimal models for international tele-ICU collaboration.
Key Findings
Effect Size: Not applicable - descriptive study
Primary Outcome: Majority of participants reported feeling well supported clinically and personally
Nnt Or Sensitivity: High acceptance and trust reported, but specific proportions not quantified
Confidence Interval: Not reported
Clinical Application
Limited by small sample size and lack of detailed implementation guidance Relevant to rural and remote ICU support initiatives, particularly for smaller hospitals lacking 24/7 intensivist coverage. May inform TGA telemedicine regulations and Medicare telehealth item development Critical care staff in resource-limited settings considering tele-ICU implementation
Abstract
OBJECTIVES: Tele-intensive care unit (TICU) networks have evolved quickly in recent years and have proved their value in providing care for the critically ill. Objective measures to assess performance and quantify success e.g. clinical and economic outcome parameters are desirable but not easily accessible in international collaboration with very diverse clinical settings and legal prerequisites. Therefore, we initiated a study to evaluate the performance in our tele-intensive care unit network. METHODS: We conducted an online survey addressing clinical staff at ten spoke sites in four countries connected to one TICU hub to assess subjective clinical benefit, acceptance and potential for improvement. RESULTS: The majority of the 30 participants felt well supported clinically and personally, with a high acceptance and trust as well as a positive working relationship in tele-medical collaboration. Ethical principles and data protection were discovered to be persistently of utmost significance in tele-intensive care unit networks. CONCLUSION: International telemedicine in critical care is perceived positively without major differences between diverse health care systems when crossing borders, showing potential for improvement to guide future clinical and research approaches. Clinical trial registiry: The study was registered on August 11th, 2023 with the German Clinical Trials Register (DRKS-IDDRKS00032246; https://www.drks.de/search/de/trial/DRKS00032246/details ).
References
- 1.Lezius, F., Steinecke, K., Herholz, A., Schüürhuis, S., Terentyuk, V., Lisnyy, I., Anvarov, K., Paruk, F., König, J. P., Grosse, J., Edel, A., Hechler, D., Spies, C. D., & Weiss, B. (2026). Survey to evaluate clinical benefits and acceptance in international tele-intensive care unit collaboration. BMC Research Notes. https://doi.org/10.1097/SLA.0000000000004078
Related Research
Journal of the American Medical Informatics Association : JAMIA
Explainable machine learning in healthcare: methods, interpretation, and applications for clinical research
2 Aug 2026
Neurosurgical review
Development and external validation of a machine learning model for predicting postoperative hydrocephalus in 1,073 posterior fossa tumor patients
31 July 2026
JAMA
Prone Positioning in Infants With Acute Bronchiolitis: The PROPOSITIS Randomized Clinical Trial
30 July 2026
This content is for educational purposes for healthcare professionals only and does not constitute clinical advice. Clinical decisions should be based on individual patient assessment, current guidelines, and appropriate specialist consultation. Editorial Standards · Privacy Policy · Terms of Service