QUMEA – a system for individual patient safety

Individual patient safety

QUMEA measures human movement in the patient room continuously and without contact. Based on this movement data, our industry-leading artificial intelligence (AI) recognises potentially dangerous situations and informs nursing staff when patients need help – depending on the individual monitoring scenario they define for each patient and room.

QUMEA recognises and informs 24/7 about:

Bed exits

Recognises bed-exit tendencies in several stages and provides information depending on the individual monitoring scenario

Falls

Care givers can intervene immediately and thus ensure the fastest possible fall rescue.

Activity & restlessness

Monitors patient activity to assess sleep quality or validate therapeutic measures, supports delirium therapy and detects sudden restlessness and agitation.

Mobilisation

Automatically detects lying positions and mobilisation in order to identify and minimise the risk of pressure sores at an early stage.

Seat monitoring

Alerts according to patient-specific monitoring scenario as soon as patients get up from chairs, wheelchairs, etc.

No bed return

Recognises when there is no return to bed at night, for example after a visit to the toilet.

Zones entry/exit

Detects when entering or leaving defined areas, e.g. toilet or patient room.

Presence

Monitors room and bed presence individually and in real time, even in shared rooms.

«As one of the first-mover clinics in Switzerland, we have been able to significantly reduce falls with QUMEA. Additionally, the system provides safety and relieves caregivers of laborious processes, giving them more time for their core tasks with patients. Patients are protected and gain autonomy. By foregoing the use of cameras, QUMEA supports our commitment to respectful patient care, as their privacy is maximally preserved. Another positive effect is the significant reduction in costs for patient sitters.»

Marco Gugolz
Clinic Director Clinic Hirslanden, Zurich

«The QUMEA architecture allows the system to be put into operation quickly and without a great need for internal technical resources. The QUMEA cloud architecture proves highest availability and the apps an exemplary user experience. Definitely an inspiration for how digital support should work in mission-critical hospital environments!»

Thomas Seiler
Head of Digitization and ICT Cantonal Hospital Aarau

«QUMEA’s early detection of potentially dangerous situations is impressive. Thanks to the system, we have been able to significantly increase patient safety. At the same time, the system enjoys full acceptance among our staff thanks to the robust alerting. The added value in in-patient care is enormous. I am convinced that QUMEA will become the standard in hospitals and that all wards will benefit.»

Cornelius-Monroe Huber
Chief Nursing Officer (CNO), Member of the Executive Board Cantonal Hospital Baselland

«Thanks to QUMEA, we have been able to reduce falls and improve patient outcomes. QUMEA is intelligent and works discreetly. We in nursing as well as the patients benefit enormously from the QUMEA system.»

Dr. Phil. Wolfgang Hasemann
Head of Basel Dementia Delirium Program University Department of Geriatric Medicine Felix Platter

«Our goal was to reduce the number of falls, especially given previous fatalities. During the test, we observed a 67% reduction in falls. QUMEA’s system is 100% anonymous and completely refrains from using cameras and microphones. The staff found the system to be simple. The early signals, which could prevent falls, were highly appreciated.»

Terese Dalåsen
Area Manager and Project Owner Västra Götaland Region

«QUMEA has become an integral part of our work processes. For our vulnerable patients, effective fall prevention is of the utmost importance. The fact that patients do not have to wear anything additional on their bodies is a further advantage. We reduce the risk for the patient and improve the treatment outcome at the same time.»

Dr. med. Bettina von Rickenbach
Deputy Chief Physician Center for Geriatric Medicine and Palliative Care, Affoltern Hospital

Safety & support for better quality

QUMEA supports carers in their daily work, for example when caring for patients with cognitive impairments or during night-time care. Digital mobility monitoring helps to manage risks, recognise hazards in good time, reduce hospital-acquired conditions and improve outcomes. For greater patient safety and more nursing support on the ward.

Fewer falls

Recognising indicators for leaving the bed, wheelchair or similar at an early stage provides a decisive time advantage and leads to a significant reduction in falls.

More efficiency

Targeted and early alerting reduces the nursing effort in the patient’s room compared to other prevention systems, such as bell mats.

Lower costs

Compared to previously used prevention measures, QUMEA has achieved cost savings of between 49 and 76%.

85 Net Promoter Score

After an initial system evaluation, the vast majority of users are clearly in favour of QUMEA.

QUMEA offers the only data protection-compliant system without a camera that is ethical and proportionate.

Interested but still unsure?

Contact us for a live demo or a reference visit to one of our customers and see the simplicity and effectiveness of QUMEA’s mobility monitoring for yourself.

Request a live demo

7. March 2025

Human Bytes and QUMEA Partner to Bring Smarter Patient Monitoring to Danish Healthcare

Human Bytes and QUMEA are joining forces to introduce radar-based mobility monitoring to hospitals and elderly care facilities across Denmark.

3. March 2025

Klinik Lengg and QUMEA: Successful partnership

Following a successful pilot phase, Klinik Lengg in Zurich is continuing to use QUMEA to provide even more comprehensive care for patients who are particularly at risk of falling.

15. January 2025

QumPreFall interim results show: QUMEA significantly reduces falls in delirium patients

The digital mobility monitoring system QUMEA, which recognises tendencies to get out of bed and falls in patients with delirium, was able to achieve a 43% reduction in falls compared to conventional methods.