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Original Contributions

Evaluation Of CPR Quality Via Smartphone With A Video Livestream – A Study In A Metropolitan Area

, MD, , PhD, , MSc, , MD, , MD ML DEAA FESC FERC FAHA & , MD
Pages 76-81 | Received 14 Dec 2019, Accepted 20 Feb 2020, Published online: 20 Mar 2020
 

Abstract

Background

Telephone-assisted cardiopulmonary resuscitation (CPR) is an effective and proven tool to improve patient survival and outcome after cardiac arrest, and is therefore recommended in international resuscitation guidelines. A new technology that provides the emergency medical services (EMS) dispatcher with a video livestream from a smartphone during telephone-assisted CPR was investigated to assess whether a correct judgment of CPR quality is feasible.

Material and Methods

After Ethics Committee approval, we conducted this study from August to September 2018 in the University Hospital of Cologne and its metropolitan area. Our study team set up a full-scale resuscitation mannequin on 54 study sites. Video telephony between caller and EMS dispatcher was established, and CPR was initiated with randomized common quality issues concerning compression frequency, compression depth, and compression point. It was evaluated whether the dispatcher recognized correct and incorrect resuscitation performance.

Results

Forty-six video calls were established successfully. EMS dispatching staff identified correct compression frequency (100-120/min) in 87.5% of the cases, too low frequency (<80/min) was correctly identified in 92%, and too high frequency (>140/min) in 58.5%, respectively. Correct compression depth (5-6 cm) was identified in 70.6%, shallow compressions (<3cm) in 92.9% and a continuous decrease of depth in 100% of all cases. Correct compression point was identified in 87.5%, incorrect epigastric compression in 92.3%, incomplete release in 58.8%.

Conclusion

A video livestream from a smartphone can support an EMS dispatcher’s assistance in resuscitation. Typical resuscitation mistakes, like incorrect compression frequency or depth, and incorrect compression points could be recognized and corrected efficiently via video livestream.

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