Evaluation of the Implementation of Automated Early Warning Scoring System in Improving Patient Safety in Inpatient Ward Kasih Ibu Hospital Denpasar

Widhyari, Kadek Dwi
Wahyudi, Bayu
Andikarya, Oke

Journal of Economics and Social Sciences
Vol. 4 No. 1 (2025): Journal of Economics and Social Sciences (JESS)

This study evaluates the implementation of an Automated Early Warning Scoring System (AEWSS) in enhancing patient safety in the inpatient ward of Kasih Ibu General Hospital, Denpasar. Using a qualitative case study approach, data were collected through in-depth interviews, FGDs, observations, and document analysis. Findings indicate that AEWSS effectively enables early detection of patient deterioration via real-time physiological parameter monitoring, accelerates medical response (from an average of 15 minutes to 5 minutes), and prevents Adverse Events. The system also improves medical staff efficiency by reducing nurses’ administrative workload by 30% and supports clinical decision accuracy through objective scoring. Key challenges include unstable network infrastructure (affecting 15% of rooms), specialist physician resistance, and uneven training. The implications highlight the need for infrastructure investment, regular training, and integrated AEWSS-Electronic Medical Records (EMR) protocols to optimize patient safety.