Hospital intensive care units are notoriously noisy, with medical equipment emitting alarms, beeps, and other alerts designed to grab the attention of overextended healthcare workers.

That constant barrage can lead to what experts call alarm fatigue, causing stress and exhaustion for doctors and nurses who must distinguish between routine signals and those indicating a patient is in urgent distress. Patients, too, often struggle to rest amid the cacophony, even though sleep is critical to recovery.

To Ophir Ronen, a serial tech entrepreneur who sold his IT alert-handling startup Event Enrichment HQ to PagerDuty, the problem sounded familiar. Ronen first encountered the ICU alarm issue while volunteering in search and rescue, and he realized that although “alarm fatigue” has been widely discussed in scientific literature, no one had yet developed a comprehensive solution.

“I thought to myself, ‘wow, we certainly experienced the problem of alarm fatigue in operations and enterprise IT—I wonder if it’s the same pattern,’” he says. 

[Image: CalmWave]

Betting the problem might have a similar fix, Ronen founded CalmWave in 2022, with early backing from the Allen Institute for AI’s incubator program. The startup aims to help hospitals silence unnecessary alarms, prioritize those that truly demand action, and build datasets that make it easier for computers to tell the difference.

Like other complex IT operations, Ronen found that critical information in hospitals is siloed across at least two systems: electronic medical records (EMR), which track diagnoses and treatments, and networks of sensors and monitoring systems that log vital signs and trigger alarms. Those monitoring data points typically never make it into EMR systems, which aren’t designed to handle that volume of information, Ronen says. CalmWave’s technology integrates both streams.

The system presents staff with a unified view of patient vital signs alongside treatment timelines, such as medication administration, reducing the need to toggle between records to assess a patient’s status. Drawing on its accumulated data, CalmWave can also recommend how to adjust alarm thresholds for specific patients, backed by clinical evidence explaining its reasoning. That might mean widening acceptable ranges to reduce unnecessary noise or tightening thresholds to catch problems earlier, according to Ronen.

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