Optimizing Patient Safety Through Digitalization Fall Risk Monitoring in Patient Wards : Implementation of THE SI-MONITOR FALL System at A Type C Hospital in Padang City

Abstract

Patient falls are among the most frequently occurring patient safety incidents in inpatient settings and remain a global priority under Patient Safety Goal 6 (SKP-6). Manual paper-based monitoring systems have critical gaps including data latency, human error, and fragmented clinical communication. Digitalization through rule-based artificial intelligence offers an integrated early warning system solution. To analyze the effectiveness of the SI-MONITOR JATUH digital fall risk monitoring information system in improving patient safety, documentation efficiency, and nurse compliance with SKP-6 standards in the inpatient wards of a type C hospital in Padang City. This study used a Project Based Learning (PjBL) design with a quasi-experimental approach. A pilot project was conducted over four weeks in inpatient ward A (16 nurses, 74 patients). Evaluation instruments included compliance observation sheets, digital system logs, and the System Usability Scale (SUS) questionnaire. Results: Implementation of SI-MONITOR JATUH resulted in a 41.5% reduction in documentation time (from 8.2 to 4.8 minutes per patient), a 60% decrease in fall incidents, an increase in safety attribute compliance from 62% to 91.3%, and a SUS score of 82.5/100 (Excellent). Calculation accuracy of the Morse Fall Scale and Humpty Dumpty Scale reached 100% (0 errors from 50 simulations). Digitalization of the fall risk monitoring system through SI-MONITOR JATUH significantly improved patient safety, nursing workflow efficiency, and STARKES SKP-6 accreditation compliance. The system is ready for full implementation across all inpatient units of a type C hospital in Padang City.