# Self-Reporting Technique-Based Clinical-Trial Service Platform for Real-Time Arrhythmia Detection
## 4 Discussion
### Benefit-Risk Assessment  
Primarily, this platform was developed for clinical-trial purposes. However, it can develop into a medical device for remote patient monitoring and diagnosis. The Food and Drug Administration (FDA) has performed benefit-risk assessment for new medical devices, and several benefit and risk factors have been proposed [37]. As a potential patient-management system, the benefits and risks of this platform were considered.  
Benefits were assessed from four perspectives: types of benefits, patient perspective on benefit, likelihood of patients experiencing one or more benefits, and benefit factors for healthcare professionals or caregivers. Type of benefits was considered on the basis of the impact on the health of the arrhythmia patients. They can monitor their ECG and check for arrhythmias in their daily lives, without having to visit hospitals. Clinicians can observe the ECG and arrhythmia-detection results in the hospital, and take proper follow-up measures if serious events happen. For instance, paramedics can be dispatched to transport a serious patient to the hospital. With such intervention, this platform would be highly valued in terms of patient perspective on benefit. To achieve this goal, the arrhythmia-detection algorithm needs to be improved, and clinicians' intervention protocols should be developed. The third benefit factor considered was the likelihood of patients experiencing one or more benefits. In 2020, over 400,000 patients came to the hospitals and were treated for arrhythmias in Korea [38]. According to performance review of potential increased use, up to 7200 patients (approximately 1.8 percent of all the patients) can connect with this platform and measure their ECG concurrently. By reducing the algorithm processing time and upscaling the platform, more patients would benefit from this platform. Lastly, reduced diagnosis time and earlier treatment can be benefit factors for healthcare professionals or caregivers.  
This platform also possesses several risk factors. The most important factor is false-positive or false-negative results. This factor is closely related to algorithm performance. If the algorithm gives a false-positive result, patients without arrhythmias might receive unnecessary treatment while unnecessary efforts of clinicians are wasted. On the other hand, if a false-negative result is generated, actual patients might not receive timely treatment, which could lead to serious conditions or death. To mitigate this risk, arrhythmia-detectionperformance should be improved and evaluated thoroughly. Distribution of nonconforming devices is another risk factor; because this platform can connect with medical devices via Bluetooth communication, nonconforming devices with the same communication protocol might access this platform. To avoid this risk, the unique device-identification (UDI) information can be utilized [39]. In 2012, the UDI system was initially established by the FDA to identify medical devices, and Korea's MFDS requires the UDI information of the approved medical devices to be submitted. If this platform can recognize the UDI information of the newly connected devices, risk regarding distribution of nonconforming devices could be prevented.