In many Indian hospitals, diligent monitoring of patients is largely focused on those in ICUs, leaving the ones in general wards vulnerable to health deterioration owing to lack of effective monitoring. Regional hospitals, often short of staff, struggle to adequately monitor patients, increasing the risk of unnoticed clinical decline.
So, how can hospitals bridge this gap, by meticulously tracking vital signs such as heart rate, respiratory rate, and blood pressure even in general wards?
Enter Dozee, India’s first AI-based contactless remote patient monitoring system. Dozee recently published a study in Frontiers in Medical Technology detailing the impact of its AI-powered Early Warning System (EWS). Conducted at King George’s Medical University (KGMU) in Lucknow, the study reveals how Dozee’s technology can predict health deterioration up to 16 hours in advance, creating a critical window for healthcare providers to intervene and potentially save lives.
With approximately 1.9 million patients in Indian hospitals’ general wards relying on periodic manual checks, Dozee, the pioneer of the AI-driven technology in the country offers a transformative solution. The innovation promises to bring round-the-clock, affordable monitoring to 95% of hospital beds.
The system is said to track metrics like alert sensitivity, specificity, response time, and healthcare activity. As per the study, it could save 21 lakh lives annually and reduce healthcare costs by INR 6,400 crore.
Dr. Jean-Louis Teboul, world-renowned intensivist and critical care expert at France’s Paris-Saclay University, while emphasising the global implications of the study, said, “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 product is currently functional across 280 hospitals including Apollo, Ramaiah, Sparsh, and Medicover Hospital in Bengaluru.
AI in Patient Care
Across the world, technology is being leveraged in a similar yet distinct way. At the University of Florida Health Center in the US, doctors are using AI to monitor patients closely. The insights gained are encouraging the development of advanced algorithms designed to deliver real-time healthcare recommendations.
For instance, a patient awaiting a lung transplant at the Health Center is placed in a high-tech ICU equipped with sensors and cameras that are monitoring crucial details like vital signs, facial expressions and movements. This is how AI continuously analyses over 350 gigabytes of patient data, detecting subtle cues like a patient’s grimace, which might indicate distress.
Funded by the US health department’s National Institutes of Health, this project aims to ease the burden on healthcare providers by allowing AI to interpret actions and present data in an accessible format.
Meanwhile, digital consultancy Netguru is changing the game with tools and resources that accelerate digital transformation. Their work empowers organisations to innovate, offering solutions that reimagine traditional processes.
One such innovation is AI-assisted patient scheduling. With an aim to tackle the frustration of long wait times and disorganised appointment systems, these algorithms analyse patient data to find the ideal time slots for each individual. This technology also allows hospitals to optimise resources, creating a smoother and more responsive flow of care.
AI in Healthcare
The AI healthcare market, valued at USD 11 billion in 2021, is expected to grow to USD 187 billion by 2030, according to Statista. This increase signals a transformative shift in the way hospitals, medical providers, pharmaceutical companies, and other healthcare stakeholders operate.
However, for organisations developing AI solutions, accessing diverse data sources remains a challenge and an expensive one.
Speaking at Cypher 2024, India’s Biggest AI Conference, Wadhwani AI CEO Shekar Sivasubramanian pointed out, “Collecting data like X-rays and MRIs needed for health-related AI innovations is costly. An X-ray copy costs INR 100, while taking a photograph of the X-ray is free.” By capturing X-rays as photographs, innovators can cut down on expenses without compromising on the data’s utility, making data collection an affordable resource for AI-driven healthcare solutions.
As a nonprofit AI institute dedicated to social impact, Wadhwani AI collaborates closely with India’s Central TB Division (CTD) to support the National Tuberculosis Elimination Programme’s AI readiness. The institute uses AI to interpret LPA blood test results, which identify drug resistance in tuberculosis patients. Each LPA strip shows a unique pattern of dark and light bands, indicating specific regions of the TB bacterium’s genome and the patient’s drug-resistance profile.
What’s Next?
Implementing monitoring systems like Dozee-EWS in general wards has shown promising results, boosting patient safety through timely alerts that allow for early detection of health deterioration. This system also provides substantial time savings, enabling healthcare providers to optimise their workflow and spend more time on direct patient care.
Even so, there is a need for advanced monitoring technologies to elevate clinical outcomes and efficiency, particularly in resource-constrained hospitals. Going forward, the study must focus on expanding these findings across varied healthcare settings, integrating additional vital signs and maximising the clinical value of these systems.
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