DIGITALIZATION OF THE EARLY WARNING SYSTEM AND HEALTHCARE WORKER COMPLIANCE
Abstract
Abstract
The digitalization of the Early Warning System (EWS) has been developed to support the early detection of patient deterioration through faster, more accurate, and integrated clinical documentation and monitoring. However, evidence regarding its influence on healthcare workers' compliance with patient monitoring remains limited. This study aimed to examine the effect of digitalizing the Early Warning System (EWS) and Maternity Early Warning System (MEWS) on healthcare workers' compliance in monitoring patient conditions. A quasi-experimental study with a one-group pretest-posttest design was conducted involving 39 healthcare workers selected using total sampling. The intervention consisted of implementing the Alamanda Warning System, while compliance was measured using a modified Morisky Medication Adherence Scale questionnaire. Data were analyzed using the Wilcoxon Signed-Rank test. The mean compliance score was 62.5 ± 27.5 before the intervention and 60.5 ± 23.9 after implementation. The analysis revealed no statistically significant difference in compliance scores before and after implementation of the digital system (Z = −0.688; p = 0.491). The digitalization of EWS and MEWS did not significantly improve healthcare workers' compliance. Continuous training, regular supervision, periodic evaluation, and organizational support are needed to optimize the integration of digital systems into routine clinical practice.
Keywords: Early Warning System; compliance; digitalization; healthcare workers; patient monitoring.
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DOI: https://doi.org/10.36780/jmcrh.v9i2.12388
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