AI-powered early warning system predicts patient deterioration up to 16 hours in advance – ThePrint – ANIPressReleases

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In a nation with 2 million hospital beds, where approximately 1.9 million patients in general wards rely on manual spot checks for their monitoring, Dozee’s AI-powered remote patient monitoring and early warning system (EWS) offers a revolutionary solution. This technology has the potential to transform care at 95% of hospital capacity, providing continuous monitoring that saves lives and ensures world-class medical care at a fraction of the cost of ICU services.

The pioneering observational study monitored more than 700 patients for 85,000 hours and demonstrated how Dozee’s continuous, contactless remote patient monitoring and early warning system (EWS) can revolutionize traditional manual processes. By sending alerts up to 16 hours before a critical event, Dozee’s system enables healthcare professionals to act sooner, improving patient outcomes and saving healthcare professionals 2.4 hours per staff member per day . The study analyzed key metrics including alert sensitivity, specificity, average time from initial alert to deterioration, and activity of healthcare professionals, providing strong clinical evidence of Dozee’s life-saving impact.

In many Indian hospitals, continuous monitoring is limited to ICUs, leaving general wards (where most patients reside) vulnerable to undetected clinical deterioration. This study demonstrates that Dozee EWS closes this gap by continuously tracking vital signs such as heart rate, respiratory rate, and blood pressure. Results showed that Dozee’s EWS predicted patient deterioration in 67% to 94% of cases, allowing healthcare providers to intervene long before conditions became critical. This early detection has the potential to save 21 lakh lives annually and reduce healthcare costs by Rs 6,400 crore.

Key findings of the study:

* Dozee EWS warned of deteriorating patient health about 16 hours in advance

* Continuous monitoring saved 10% of healthcare professionals’ time, equivalent to 2.4 hours per day.

Dr. Himanshu Dandu, Professor, Department of Medicine, KGMU, emphasized the potential of the technology to improve critical care in resource-limited settings. “This system enables early detection and continuous monitoring of patients, providing a scalable and affordable solution tailored to the demands of healthcare systems facing large numbers of patients. “The ability to detect signs of deteriorating patient health can significantly improve their survival rates.”

Dr. Jean-Louis Teboul, a world-renowned intensivist and critical care expert from Paris-Saclay University, emphasized the global implications of the study: “What we have achieved in India has the potential to reshape healthcare globally. . The challenges may differ, but the need for equitable, timely and affordable care remains universal.”

“The results of this study confirm what we have always believed: this real-world evidence demonstrates technology’s ability to transform healthcare, making it more efficient, accessible and equitable,” said Gaurav Parchani, CTO and co-founder of Dozee. . “We are not just solving a problem for India, we are laying the foundation for global health solutions.”

The study, authored by a distinguished team of experts from around the world, including Dr. Himanshu Dandu and Dr. Ambuj Yadav of KGMU, along with Dozee’s clinical research team: Gaurav Parchani, Dr. Kumar Chokalingam and Pooja Kadambi, Dr. Rajesh. Mishra, intensivist and former president of ISCCM, and Dr. Ahsina Jahan, deputy medical director in charge of ICU and Emergency, Bangladesh. It has attracted international attention with contributions from Dr. Jean-Louis Teboul of the Paris-Saclay Medical University and Dr. Jos M. Latour of the University of Plymouth, United Kingdom. The study findings emphasize that Dozee healthcare AI offers more than a national solution; addresses global gaps in healthcare. Traditional models are proving unsustainable and Dozee’s system provides a simple, scalable and affordable solution that not only digitizes healthcare but could also serve as a model for global adoption.

Publication details: doi: 10.3389/fmedt.2024.1436034

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