Type of Innovation
The proposed innovation is the implementation and utilization of a cardiac early warning system in order to design more preventive and outcome-improving practices. The current technology can enable more opportunities for early intervention strategies, where gradual or sudden changes in cardiac output can be measured and monitored in a consistent manner. In other words, the given innovation will greatly improve the overall outcome of ischemic heart disease and cardiac arrest since the technology will warn medical specialists preliminary. This will provide more valuable time to incorporate more effective preventative and intervention strategies in a timely manner. Therefore, one can argue that cardiac early warning systems integration in healthcare facilities will be a key to avoiding more severe and deadly complications associated with both chronic and acute cardiovascular problems.
The proposed innovation tackles the key problems in healthcare, such as basic monitoring systems, inexperienced EMT personnel in reading ECGs, communication challenges between EMT and ED staffs, and delay car of ACS in critically ill patients. The innovation is an early cardiac warning system, which eliminates the above mentioned issues by enhancing the existing monitoring system and expediting the case ACS patients, and it also enables early warning system prior to patient’s arrival in ED. Although it can come in many forms, such as mobile wearable devices, the core concept lies in innovative technology, which detects any cardiac abnormalities before a medical specialists check themselves or patient experiences complications. In other words, high-risk patients are constantly monitored for possible infractions rather than being periodically monitored in the conventional system.
Rationale/Justification
The system of early cardiac warning can be highly useful and effective because many developed nations are already using similar technologies in both healthcare related facilities. More specifically, early cardiac warning system enhances the existing monitoring system and expedites the case ACS patients. In addition, it also enables early warning system prior to patient’s arrival in ED. EMT preliminarily suspects myocardial infraction and contacts a suspected patient, which is followed by ED nurse notifying ED physician, who read ECG, and STEMI activates Cardiology and Cath lab. The reason for the overall use of these systems by developed countries is manifested in the fact that they allow to spot emergencies earlier, and thus, reduce mortality (Ye et al., 2019). For example, in the United States, in two acute hospitals, which are Fairview Hospital and Berkshire Medical Center, the use of cardiac early warning systems resulted in major positive changes, which manifested in the fact that the warning was delivered at least 40.8 hours before a fatal outcome (Ye et al., 2019).
Another case from Taiwan shows that implementing cardiac early warning systems alongside mobile health technologies resulted in 88% accuracy of effective predictive capabilities of the proposed technology (Sahoo et al., 2017). Similarly, a case from Taiwan also shows that utilizing these systems alongside wearable devices led to patient satisfaction and patient attitudes were improved, which also affected the aspect of adherence and collaboration (Lin et al., 2018). A more comprehensive study’s findings indicate “that the probability of detecting one or more abnormal ECG beats among the first three occurrences is higher than 99.4% with a very low false-alarm rate” (Kiranyaz et al., 2017, p. 1). In other words, the current state of technology is highly precise. In South Korea, a study conducted in Mediplex Sejong Hospital and Sejong General Hospital, which uses the proposed system, shows that the main issue with these systems, such as low sensitivity and false alarms, can be avoided, where the researchers state that “the deep learning–based early warning system reduced the number of alarms by 82.2%, 13.5%, and 42.1% compared with the modified early warning system, random forest, and logistic regression, respectively, at the same sensitivity” (Kwon et al., 2018, p. 1). These early warning systems can be highly useful among all patient categories (McLellan et al., 2017). Therefore, these cases from different nations showcase the fact that these technologies can be highly useful if implemented in conjunction with mobile or wearable devices. However, cardiac early warning systems on their own can still be highly effective at preventing and reducing death rates.
On the basis of the literature analysis, it is safe to state that the integration of cardiac early warning systems will lead to positive outcomes, which can be further improved through the use of wearable and mobile health-related devices. It also improves patient satisfaction and patient outcome levels by a significant margin. The South Korean example demonstrates that substantial modifications and enhancements can be made to the software, which means that the overall result will be compounded since such a technology can be improved dualistically (Kwon et al., 2018). In other words, a healthcare facility should be interested in acquiring and utilizing the cardiac early warning systems in order to introduce comprehensive and cumulative enhancements in the overall operation of such a facility.
References
Kiranyaz, S., Ince, T., & Gabbouj, M. (2017). Personalized monitoring and advance warning system for cardiac arrhythmias. Scientific Reports, 7(1), 1-8. Web.
Kwon, J., Lee, Y., Lee, Y., Lee, S., & Park, J. (2018). An algorithm based on deep learning for predicting in‐hospital cardiac arrest. Journal of the American Heart Association, 7(13), 1-12. Web.
Lin, W.-Y., Ke, H.-L., Chou, W.-C., Chang, P.-C., Tsai, T.-H., & Lee, M.-Y. (2018). Realization and technology acceptance test of a wearable cardiac health monitoring and early warning system with multi-channel MCGs and ECG. Sensors, 18(10), 3538. Web.
McLellan, M. C., Gauvreau, K., & Connor, J. A. (2017). Validation of the Children’s Hospital early warning system for critical deterioration recognition. Journal of Pediatric Nursing, 32, 52–58. Web.
Sahoo, P., Thakkar, H., & Lee, M.-Y. (2017). A cardiac early warning system with multi channel SCG and ECG monitoring for mobile health. Sensors, 17(4), 711. Web.
Ye, C., Wang, O., Liu, M., Zheng, L., Xia, M., Hao, S., Jin, B., Jin, H., Zhu, C., Huang, C. J., Gao, P., Ellrodt, G., Brennan, D., Stearns, F., Sylvester, K. G., Widen, E., McElhinney, D. B., & Ling, X. (2019). A real-time early warning system for monitoring inpatient mortality risk: Prospective study using electronic medical record data. Journal of Medical Internet Research, 21(7), e13719.