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Completed

NCT Number: NCT05391334

Early Fall Risk Detection and Fall Prevention Among Inpatients With Delirium

During delirium patients are at risk of severe harm due to unattended bed-exits resulting in falls. This research intends to explore how effective alarming contact mats (CareMat®) in comparison to contactless bed-exit alarming devices (Qumea®) are to reduce the risk of unattended bed-exits and falls.

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Key information

Age range

65 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Universitäre Altersmedizin Felix Platter

Basel, 4055, Switzerland

About this study

Delirium is a neuropsychiatric disorder with a sudden and reversible decline in attention and cognition due to a medical condition.8 Delirium is associated with emotional distress for patients, their relatives and medical staff.3-5 During delirium, patients are at risk of severe harm due to unattended bed-exits and subsequent falls.6, 7 As worldwide strategy, sitters are used for the prevention of harm in patients with delirium. However, evidence of the effectiveness of sitters is scant.9 A newly designed specialised acute care unit for older patients with delirium, the FELIX PLATTER delirium unit (DelirUnit), strives to overcome the aforementioned shortcomings. On the DelirUnit there are no physical barriers such as bed rails to prevent patients from bed-exits. Floor beds minimize injuries when patients leave their beds unattended. Specialised nurses and nursing aides care for this vulnerable patient group. Sitters are banned. As an alternative to sitters, nurses are informed about patients' intended bed-exit by electronic alarming contact mats at the bedside or in front of beds (CareMat®) or by a novel contactless radar-based bed-exit monitoring system (Qumea®). Up until now, evidence for the effectiveness of technical devices for fall risk prevention is low. This research intends to explore how effective contact mats (CareMat®) or contactless bed-exit alarming devices (Qumea®) are in fall risk detection and fall prevention.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Admission at or transferal to DelirUnit. During Covid pandemic, patients will be enrolled into the study after the second negative Covid swab (PCR).

Exclusion criteria

Patients who have been sectioned and must be treated in a facility, whether they agree or not (under the mental health act) (Fürsorgliche Unterbringung).

No proxy consent available due to language barriers;

Missing legal proxy in case of lacking family network

Treatment and study plan

Qumea

Device

Contactless motion sensor (Qumea®) for bed-exit detection in combination with Qumea fall detection.

Primary outcomes

  1. Falls

    Time frame: 6 months

    Number of patient falls in patient room

Secondary outcomes

  1. Bed-exit patterns

    Time frame: 6 months

    Qumea® provides the following bed-exit pattern categories: 'STANDING', 'SITTING, 'LYING' oder 'OUT_OF_BED' .

    Unit is number/percentage of bed-exit patterns. Artificial intelligence algorithms provide automatized detected bed-exit patterns by a three dimensional radar (Qumea®)

  2. Nurses' workload

    Time frame: 6 months

    Workload is defined as the time in minutes per patient and per day (24-hour period) that a nurse is present in each patient's room. This is measured as the time between activation (nurse enters room) and deactivation (nurse leaves room) of the Hospicall (the hospitals' patient call system) presence button by the nurse in each patient's room. Hospicall automatically generates a time stamp in the logbook of the Hospicall operating system when the presence button is activated and deactivated.

  3. Time to confirm a CareMat® / Qumea® warning by nurse presence in room

    Time frame: 6 months

    Time difference in seconds between timestamps from onset of warning and confirmation of warning with presence button in patient room of bed-exit warning from bed-exit surveillence systems (Qumea® or CareMat®) to Hospicall (a decentralised, scalable patient call system).

    It is the time a nurse needs to confirm a bed-exit warning from the bed-exit surveillence systems.

  4. Delirium severity

    Time frame: 6 months

    Delirium severity is a score between 0 and 39 points on a 13-item 4-point (0-3) Lickert scale, as measured with the Delirium Rating Scale Revised 98 (DRS-R-98). A cut-off score of 15.5 points indicates delirium. The higher the score, the more severe is the delirium. For the prediction models, the DRS-R-98 scores (1) at admission, (2) the mean values of the course of delirium and (3) the difference between admission and discharge will be calculated. The measurements are conducted by the research team (PI or research assistants) during the stay on the delirium unit (on Mondays, Wednesdays and Fridays) and on the day before discharge.

  5. Delirium duration

    Time frame: 6 months

    To determine the duration of delirium, the presence and/or severity of delirium is first measured with the modified Confusion Assessment Method for the Emergency Department (mCAM-ED). The mCAM-ED provides the following categories: (0) no delirium (1) probable delirium (2) definite delirium. Duration of delirium is measured in days between the first delirium positive mCAM-ED assessments (category 1 or 2) and the last delirium positive (category 1 or 2) mCAM-ED assessments. The mCAM-ED assessments are conducted by the research team (PI or research assistants) Mondays, Wednesdays and Fridays and on the day before discharge.

Sponsors and collaborators

Lead sponsor

University Department of Geriatric Medicine FELIX PLATTER

Other

Collaborators

  • University of Basel
  • Velux Fonden

Registry information

Official study title

Exploration and Comparison of Novel Technology-supported Methods for Early Fall Risk Detection and Fall Prevention Among Inpatients With Delirium

Acronym: QumPreFall

Important dates

Study start
2022
Primary completion
2024
Study completion
2024
First posted
May 25, 2022
Registry last updated
May 19, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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