Early Warning System Safeguarding Patient Lives

Abstract

Disease progression often differs among patients. According to study findings, changes in vital signs, blood oxygen saturation, and consciousness are each related closely to acute deterioration in disease status (Sutherasan et al., 2018). The early warning system (EWS) is a predictive approach to detecting deterioration in disease condition based on the observation of slight variations in patient vital signs and clinical symptoms (Smith et al., 2014). Most patients experience changes in specific physiological variables before experiencing a cardiac arrest. The implementation of a comprehensive EWS facilitates the early identification and prevention of serious adverse events such as unexpected cardiac arrest and death, and may help reduce the risk of other unexpected events as well (Gerry et al., 2017). For medical team members, the use of EWS not only permits the detection of changes in patient condition at an early stage but also allows healthcare workers to respond more proactively and effectively. Moreover, EWS has been shown to improve communication, increase cooperation, and strengthen personal responsibility among healthcare workers (Burns et al., 2018). In summary, implementing EWS allows the prompt initiation of appropriate patient treatment and helps improve patient-care outcomes. While recognizing the importance of incorporating EWS into patient care in clinical and home-based institutions as an important strategy to protecting the lives of patients, appropriate standardized warning systems must be tailored to address different disease characteristics. Changes in patient condition are traditionally addressed through nursing assessment followed by physician notification and response. However, this process may be affected by factors such as assessment accuracy, cultural differences, confidence, and past experiences that may result in decision-making errors (Wood, Chaboyer, & Carr, 2019). The integration of EWS and medical informatics technology is expected to reduce the risks of human-interpretation-related omissions and errors (Downey, Tahir, Randell, Brown, & Jayne, 2017). Although the use of medical informatics technology to enhance EWS remains in its infancy, this will certainly be one of the future trends in patient care. The articles in this issue, in addition to introducing EWS, elucidate the current application of EWS in clinical critical conditions and introduce how informatics technology is being combined in home EWS applications. These articles comprise a rich body of information on EWS that may referenced in clinical nursing care, home care, education, and research.