New Delhi: Across India’s vast healthcare network, which relies heavily on more than two million hospital beds, traditional methods of monitoring patients in general wards rely heavily on regular manual checks. This conventional system often causes a delay in detecting deterioration of healthleaving many vulnerable patients at risk.
A recent study published in Frontiers in Medical Technology (FMT) indicates that this scenario could soon change, as an AI-based technology Early warning system (EWS) has shown promising potential to detect early signs of deteriorating health up to 16 hours in advance. Made in King George Medical University (KGMU), the study highlights the benefits of continuous health monitoring in non-ICU settings, where periodic spot checks have historically limited early intervention.
The AI-powered EWS, which continuously monitors vital signs, issues alerts to healthcare providers long before a critical emergency occurs. This early warning could save lives, enable faster responses and transform treatment approaches on general wards.
The study suggests that healthcare workers will also benefit, as the system could reduce their daily workload by approximately 2.4 hours per person. More than 700 patients were monitored for more than 85,000 hours, and EWS alerts demonstrated high sensitivity, specificity, and timely response capacity.
Dr Himanshu Dandu, Professor, Department of Medicine, KGMU, said: “The ability to detect signs of deteriorating health of the patient can significantly improve their survival rates.”
The results showed that the EWS successfully predicted health problems in approximately 67 to 94 percent of cases. Based on these findings, researchers estimate that implementation of the system could save up to 2.1 million lives annually and reduce healthcare costs by approximately Rs 6.4 billion.
