Ascom’s Dr. Ariana and the great clinical data hunt

Data generation in a real hospital setting

But how is data generation benefitting hospitals in the here and now? Ariana’s answer is short and powerful: “it gives them certainty.” What she means is that all too often the impact of a technical investment is measured in vague or subjective terms. For instance, staff may report that responding to alerts ‘feels’ faster and easier following the installation of a new system. That may very well be the case. But it’s hardly the solid data that hospital managers can call on when planning new investments, or assessing the effectiveness of significant capital expenditures.

“What hospitals require,” adds Ariana, “is absolutely trustworthy data that is gathered from the system as it is actually used—not from a lab setting, or a digital model, or from a vendor’s projections.” To illustrate her point, she refers to last year’s data generation project at the ICU at Central Ostrobothnian Central Hospital (CH) in Kokkola, Finland. Like many hospitals, CH is moving away from open ICU layouts to single-patient rooms. “Single ICU rooms,” explains Ariana, “offer tremendous benefits for patients, giving them a sort of healing cocoon that can significantly cut the length of their stays in the ICU.”

However, every action has a reaction. And with single-patient ICU rooms, that reaction is often increased patient exposure to prolonged and loud noise from the array of alarms and alert notifications typically found in modern ICUs. Also, staff have to be able to receive alarm notifications, even when they can’t see patients. Ironically, 85 -90% of all ICU alarm notifications are non-critical—they don’t require immediate staff intervention. Anything that can quietly yet reliably filter and distribute alerts to staff is key to reducing noise, to the benefit of patients and staff alike.

Data shows lower noise, fewer alerts in new ICU

When in 2024 CH replaced its five-bed open ICU with seven single-patient rooms, it took the opportunity to deploy an advanced Ascom Clinical Alarm and Alert Management solution—and Ariana and the Data Generation team was informed. “Fortunately, we were involved at an early stage says Ariana. “Another positive factor was the hospital’s enthusiastic embrace of the data-gathering exercise. The ward management were of course keen to see how the solution improved some key metrics, and they extended us every possible assistance.”

When the project’s findings were published in early 2025, the data supported one incontrovertible fact: After installing the Ascom solution, the proportion of louder alarm notifications above 50dB at patients’ bedsides decreased from 56% to 24%, contributing to a quieter environment.

The Ascom solution resulted in 6% of notifications recorded during the day (8:00 – 20:00) being well below 40dB—an important move towards the ICU noise level of around 40dB recommended by the World Health Organization (WHO). Finally, a rigorous analysis of filtered alarm data showed that over a 30-day period, the Ascom solution reduced by 80% the number of non-actionable alarm notifications from patient monitors reaching nurses, from 32,000 to only to only 4,800 alerts.

“These are excellent results,” says Ariana. “They prove that the solution is working, and that it is delivering an improved healing environment for patients, and a better workplace for ICU staff.” But she is also keen to stress that data generation provides so much more than proof of performance. That’s because the wealth of data gathered by her team also shows where and how the solution can be optimized, both in the subject hospital’s deployment, and also for future Ascom systems. “It’s really quite simple,” adds Ariana in conclusion. “Solution optimization is a non-stop process, and personally, I’m thrilled to help generate and analyze the data that fuels it.”