<![CDATA[Sudden death due to illness in the workplace remains a critical occupational health challenge, particularly in high-risk industries where workers are exposed to complex operational conditions. The increasing occurrence of illness-related fatality incidents highlights the need for predictive approaches that integrate occupational health and operational risk management. This study aimed to develop a predictive analytics model for assessing sudden death risk among workers at PT XYZ by examining the effects of Fit-to-Work (FTW) status, workload, and extreme work environments, as well as developing an early warning scoring system. The study employed a quantitative approach using a case-control design based on secondary data from Medical Check-Up (MCU) records and workplace sudden death investigation reports. A total of 581 worker records were analyzed, consisting of 65 illness-related fatality cases and 516 control samples, using chi-square analysis and binary logistic regression. The results showed that shift work significantly increased sudden death risk (adjusted odds ratio [AOR] = 18.06; p < 0.001), while outdoor work environments also contributed significantly (AOR = 2.60; p = 0.004). FTW status showed a protective tendency but was not statistically significant. The developed Illness Fatality Risk Score (SRIF) demonstrated good predictive performance, with an area under the curve (AUC) value of 0.840. In conclusion, workload characteristics and environmental exposure were important predictors of workplace sudden death risk, and SRIF could serve as a practical early warning tool to support proactive occupational health risk management.]]>
