“The patients in our hospitals are becoming more acute with each passing decade,” Tom McCoy, MD, medical director of biomedical engineering at Massachusetts General Hospital, told Becker’s. “When we look at acute care, it’s very obvious that medical devices are a critical component of delivering very high-acuity medical care.”
Hospitals currently receive a vast amount of patient information from multiple sources, including EHRs, medical devices and lab results. However, these systems often do not integrate seamlessly, leading to fragmented data that makes it challenging for physicians to get a comprehensive view of a patient’s condition.
To address this issue, Philips and Mass General Brigham are developing a system to consolidate real-time patient data into a single platform. Philips’ technology will collect live data from devices such as ventilators and patient monitors, integrating it with medical records. AI will then analyze this data and send automated alerts if a patient’s condition changes, allowing physicians to respond more quickly.
Meanwhile, Mass General Brigham will contribute its expertise in engineering, AI and clinical care to develop tools that identify patterns in patient data. These tools aim to detect early warning signs of deteriorating health, enabling earlier intervention and potentially preventing complications.
“When you walk into a modern, high-acuity patient room, you’ll see that a single patient is supported by multiple medical devices. For software to truly support the patient, it must integrate data flows from all these devices in real time. That requires a vendor-neutral medical device integration system, where data from physiological monitors, ventilators and other devices can be shared on the same computational platform,” Dr. McCoy said. “When we conducted our market analysis in 2017, the Philips Capsule system stood out as the best solution for mobilizing data from high-acuity settings. Over time, we’ve seen that this data provides valuable insights into patient conditions. However, the challenge lies in maintaining the complex software environment behind the commercial product. The Philips Capsule system collects the data, but we need a computational engine to process it, generate insights and support clinical decision-making.”
This partnership focuses on building this next layer—the system that links and analyzes these signals in real time.
“To use an airline analogy, it’s like ensuring that a check engine light and a low fuel alarm aren’t just separate alerts but are analyzed together to detect discrepancies in fuel consumption,” Dr. McCoy said. “This next step allows us to integrate and compute over multiple signals, offering clinicians a clearer picture of a patient’s condition.”
One of the initial research initiatives of this partnership focuses on real-time cardiac monitoring.
“The goal is to detect early signs of decompensation in patients on cardiac monitors in acute care. Using supervised machine learning, the system will analyze cases where patients required rapid response or resuscitation to predict future deterioration,” Dr. McCoy said. “Let’s use the markers from our existing healthcare system that indicate a person has gotten dramatically sicker and try to get advanced notice on impending dramatic sickness in our future patients.”
By combining AI-driven insights with real-time data, this partnership aims to set a new standard for patient monitoring in high-acuity settings, improving outcomes and response times.