Unlocking AI's potential in patient monitoring

Healthcare is a data-rich environment. The average hospital generates around 50 petabytes¹ of data each year, yet less than 3%² of it is ever effectively used. For years, the cost and complexity of storing and accessing high-fidelity, continuous data – like patient waveforms – was a major roadblock. That wasted data was a missed opportunity.

But that’s all changing. With modern cloud architectures and improved interoperability, we can now harness this data, turning it into a strategic asset that fuels smarter, more proactive care.

Patients in a hospital are surrounded by technology – monitors, ventilators, IV pumps – all generating a constant stream of valuable information. The challenge has been that this data often lives in separate, proprietary systems, making it difficult for clinicians to get a complete view of their patient.

Our monitoring ecosystem platform is designed to solve this problem. By integrating data from various devices and systems, regardless of the vendor, we create a "single pane of glass." This provides a complete, real-time view of the patient, allowing for faster, more confident decisions.

We’ve moved beyond the days when rich waveform data was discarded after a week. With our Clinical Insights storage in the Philips Cloud, we can preserve high-fidelity, vendor-neutral data for up to a year or longer. This creates a secure, scalable data lake that health systems own and control, opening up new possibilities for research, root cause analysis and the development of predictive AI tools.

Nowhere is the impact of AI more evident than in cardiac care, where early detection can save lives. The 12-lead ECG, one of the most common procedures in medicine, has become a powerful tool for AI-driven diagnostics.

By leveraging decades of historical ECG data, AI algorithms can detect subtle patterns that might be missed by the human eye. This is already improving diagnostic accuracy and helping clinicians identify cardiac issues earlier than ever before. For example, a simple 12-lead ECG at the bedside can now be layered with predictive diagnostics in seconds. This isn't a future concept; it's happening right now. AI is helping to personalize treatment plans and improve outcomes by providing a deeper understanding of each patient's unique cardiac history.

Our goal is to adopt disruptive technology without disrupting clinical workflow. Take a common scenario: a cardiologist is called for a consult on an abnormal ECG. It can take up to 45 minutes just to gather the necessary data from multiple, disconnected sources.³

Philips’ cardiology vision is to automate this process to create a system that pulls serial ECGs, echo results, medication lists and comorbidities into a single, comprehensive report. The cardiologist can then focus on diagnosis, not data retrieval. They can review findings, see the clinical logic the AI used, and access the source data, all within one interface. This builds trust and transparency while giving clinicians back their most valuable resource: time.

The potential for AI is only growing. We're already seeing momentum in diagnostic cardiology. One study showed that AI could predict the onset of atrial fibrillation up to two weeks before it occurs by analyzing continuous ECG biomarkers.

Imagine a future where we can:

This is the future we’re building – an open informatics platform, allowing hospitals to deploy their own custom algorithms, leverage Philips-developed solutions or integrate third-party tools.

Let’s look at a practical example of what this vision could be . A patient is in the ICU post-surgery. While her nurse is away from the bedside, an AI algorithm detects an increased risk of bleeding and sends an alert directly to the nurse's mobile device. The nurse returns to the room, reviews a detailed event summary on the bedside monitor, and escalates the finding to the intensivist. The bleeding is confirmed with an ultrasound, and Sarah is sent back to surgery, preventing a more devastating outcome. This is the power of AI in action – supporting clinicians and protecting patients.

As we unlock AI's potential, we’re committed to ethically and responsibly deploying it. Our CEO, Roy Jakobs, co-chairs the U.S. National Academy of Medicine’s Steering Committee on AI Code of Conduct. Together with our partners, we’re developing a framework to ensure the equitable, safe and responsible use of AI in healthcare.

AI isn’t here to replace clinicians. It's here to empower them. By designing intelligent, supportive and intuitive technology, we can alleviate burdens, augment clinical abilities and unlock a new future of proactive, personalized healthcare.