3 ways to improve patient care in 2025 and beyond

We’re swimming in data-rich information pool, and for anyone who thinks that’s overstating it, consider this statistic I shared during my session: nearly 70% of hospital patients now have multiple chronic conditions [1]. Every one of those conditions generates its own stream of data, and clinical teams are drowning in it. On paper, all this information is supposed to lead to better precision care. But in practice, it often bogs down workflows and leaves staff struggling to make sense of it all.

Here’s the kicker, though – 66% of healthcare leaders acknowledge that this data complexity is fueling staff burnout [2]. When clinicians are burned out, patient care suffers, operational bottlenecks multiply and we see that trickle-down effect across the entire organization.

What I think needs to happen:

We need to do more than just collect data – we need to make it useful and manageable. Investing in tech platforms that centralize and standardize these streams is a must. Systems that can filter out the noise and turn data into actionable insights will give our teams the clarity they so desperately need.

The cognitive load we’re placing on our clinicians is simply staggering. If you were at HIMSS, you’ll remember me pointing out that clinicians handle an average of 150–350 alarms per patient every day [3]. Every. Single. Day. And the majority of those alarms are non-actionable.

It’s a scenario we’ve all seen play out. The constant noise creates fatigue, and that fatigue makes it harder for clinicians to discern between what’s routine and what’s a real emergency. When alarms get ignored or muted, patient safety ends up on the line, and no one feels good about that.

How we can lighten the load:

This is where AI can be a game changer. I’m genuinely excited about the potential of patient-specific alarm thresholds, where settings are customized based on factors like medication profiles and bedside monitors. This kind of tailored approach can significantly reduce non-essential alerts, allowing clinicians to focus where it actually counts.

I’ll be honest, not all the data-related news I shared was heavy. There’s a huge bright side here. If we’re strategic about it, all this data we’re wrestling with can actually work for us instead of against us.

Before we can even begin to talk about leveraging AI in healthcare, we must first establish a strong foundation of data. This starts with collecting comprehensive patient monitoring data – not just gathering it but also using tools that can transform this data into meaningful insights.

Philips has unlocked this capability through our Clinical Insights Manager, which enables hospitals to store patient monitoring data securely in the cloud. By leveraging data-driven tools such as Alarm Insights and Telemetry Insights, hospitals can gain a clearer understanding of trends within their specific patient populations. These insights empower care teams to standardize alarm settings and optimize clinical workflows.

Building this solid foundation of standardized data and insights paves the way for the adoption of clinical decision support (CDS) tools. Philips solutions include embedded CDS capabilities like multiparameter scoring, advanced event surveillance, and Alarm Insights – tools designed to help clinicians make more informed decisions in real time.

The effective adoption of these CDS tools is what truly enables the future of AI in healthcare. AI isn't the starting point – it's the next step, and it can only be successful if built upon a reliable, insight-driven foundation.

My recommendation:

Focus on platforms that can integrate AI-driven analytics into your current workflows, but make sure they’re scalable. You don’t want a piecemeal solution that works today but doesn’t grow with your needs. And don’t forget to loop in clinical and IT leadership early on. Change management is a team sport, and their buy-in will be essential.

If there’s one takeaway, I hope you remember here, it’s that the challenges we’re facing aren’t isolated. Data complexity, alarm fatigue, clinician burnout…these are all intertwined, and trying to address them in silos simply won’t work.

The time to act is now, and the actions need to be bold. By leaning into tools like interoperability, AI and standardization, we can relieve the burdens on our staff, improve patient outcomes and make our organizations more resilient.

Your teams are ready for the solutions that will tackle these challenges head-on. The only question is, are you ready to give them what they need? I believe you are.