Bedside monitors produce waveforms, numerics and alarms faster than care teams can absorb them. Turning that stream into real-time insight is the challenge now facing AI in patient monitoring, and most organizations are not yet positioned to meet it.
In a Becker’s Healthcare and Philips survey of 151 hospital and health system leaders, 33% reported only partially connected monitoring systems and 15% still rely on limited integration or largely standalone systems. Fourteen percent describe their data infrastructure as early-stage for AI.
Belief is running well ahead of commitment. Seventy-two percent of leaders expect AI to have a significant impact on patient monitoring within five years. Only 16% plan significant investment in the next 12 months, and just 10% back it with dedicated funding and leadership.
The report lays out what has to be built first: capturing physiologic data consistently, preserving its clinical context, connecting it across systems and governing it where decisions get made.
Inside the report:
- The two barriers leaders cite most and why both describe the same underlying problem
- What diagnostic ECG has already proven about running AI on standardized physiologic data
- The AI capabilities leaders rank highest, from patient prioritization to fewer nonactionable alarms
- Why interoperability and clinician training rank as the top two preparation priorities for the next two years