Data-filtering alarm system

If an alarm goes off while the nurse is taking care of a patient in another room, it can be difficult to decide which patient to prioritise. Maybe the patient’s condition has acutely worsened or maybe it is just a low battery on one of the medical devices.

AIM

This project aimed to develop a digital system that enabled the monitor devices and machines to send alarms to the staff’s smartphones, while filtering data so that each type of alarm got its own sound. With this alarm system, the staff could distinguish between technical alarms and clinical alarms by the sound coming from their work phones. The nurse could then make an objectively based decision about which patient to attend to first.

Furthermore, the alarm system meant to free time for the nurses to do other tasks, as they could now observe the patients from a distance. The nurse caould, for example, go to the medicine room with no worries, because she would know that she would be alerted instantly if an alarm went off. She would also know exactly which bed to hurry to, in order to give the required assistance.

In addition to that, the system was also meant to provide a more calm environment for the patients. It would be possible to turn down the sound from the equipment, and, with newer equipment, even turn off the display so the patients could have silence and darkness at night.

RESULTS

The system did not have the desired effect. The staff found it difficult to use due to technical problems during the test period and because the department was affected by covid-19 and the nursing strike.

However, the staff found it positive that the system provides fewer noise nuisances for the patients, that they can hear the alarm even though they are some distance from the patient, and they liked the possibility of being able to differentiate the type of alarm. In practice, however, it did not work in the department.

PARTNERS

The project was carried out at the Department of Gastroenterology at OUH, in collaboration with the companies Cambio and Ascom. It was a part of the large innovation project Digital Vision.

EXTERNAL FUNDING

The project was financed by the OUH Innovation Fund.