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DIANA: Digital Intelligent Assistant for Nursing Application

Sponsor
Geriatrische Klinik St. Gallen (Other)
Overall Status
Not yet recruiting
CT.gov ID
NCT04393272
Collaborator
(none)
25
Enrollment
1
Location
35.9
Anticipated Duration (Months)
0.7
Patients Per Site Per Month

Study Details

Study Description

Brief Summary

This is an observational study that intends to compare falls or fall-risk related alarms derived from a three-dimensional sensor system with the clinical reality definded by attending nurses.

Condition or Disease Intervention/Treatment Phase
  • Device: Three dimensional sensor system designed for fall detection (Fearless)

Detailed Description

Three dimensional sensor technology (3DS) is available for fall detection and fall prevention (e.g. unwanted getting up in persons with risks for frequent falls) in several institutions in Europe and Switzerland. 3DS are capable to analyze completely anonymized data and alert nurses towards a dangerous (fall) or potentially dangerous (getting out of bed) event during day- and nighttime. Multi-sensor technology has been applied to assess activities of daily living in persons cognitive problems living at home. To our knowledge, 3DS technology has not been examined as part of a structured clinical protocol. In addition, the combination of two digital technologies (3DS and a server based software) as an integrative platform could help to develop algorithms to analyze complex human activities such as using a toilet. Automated analyses of such complex activities have the potential to support nursing staff in the future.

Study Design

Study Type:
Observational
Anticipated Enrollment :
25 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
Digital Intelligent Assistant for Nursing Application Evaluation of 3-Dimensional Sensor Technology in Long Term Care and Acute Geriatrics. A Single Center Observational Study
Anticipated Study Start Date :
Aug 1, 2020
Anticipated Primary Completion Date :
Apr 30, 2023
Anticipated Study Completion Date :
Jul 31, 2023

Outcome Measures

Primary Outcome Measures

  1. Falls detection rate [Through study completion, an average of 6 months]

    Number of falls detected by the system compared to falls detected by nursing staff members

Other Outcome Measures

  1. Assessment of toileting [Through study completion, an average of 6 months]

    3d sensor system data will be used to develop an algorithm for a complex activity such as using a toilet. The senors results will be compared with a Nurse led 12 step observation protocol. Parts of the activity model include: (1) enter the room, (2) go to the toilet, (3) take off clothes, (4) sit on the toilet, (5) clean oneself, (6) stand up, (7) get dressed, (8) flush the toilet, (9) go to the sink, (10) wash hands, (11) dry hands, (12) leave the room, as well as emergencies.

Eligibility Criteria

Criteria

Ages Eligible for Study:
75 Years and Older
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No

Inclusion criteria Informed consent given by person or caregiver Patients admitted

  • with or without cognitive decline for any reason

  • with acute and/or chronic conditions

  • after any kind of surgery

Exclusion Criteria:
  1. For Falls assessment by 3D sensors:

• Based on the multifactorial risk for falls there are no exclusion criteria for falls assessment

  1. For the development of toileting algorithm:

  • severe urine or fecal incontinence

  • permanent indwelling urinary catheter

  • permanent urinary or bowel stoma

Contacts and Locations

Locations

Site City State Country Postal Code
1 Geriatrische Klinik Sankt Gallen SG Switzerland 9000

Sponsors and Collaborators

  • Geriatrische Klinik St. Gallen

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
Thomas Munzer, MD, PhD, Chief of Geriatrics, Geriatrische Klinik St. Gallen
ClinicalTrials.gov Identifier:
NCT04393272
Other Study ID Numbers:
  • BASEC 20-00904
First Posted:
May 19, 2020
Last Update Posted:
Aug 7, 2020
Last Verified:
Aug 1, 2020
Individual Participant Data (IPD) Sharing Statement:
No
Plan to Share IPD:
No
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Keywords provided by Thomas Munzer, MD, PhD, Chief of Geriatrics, Geriatrische Klinik St. Gallen
3D sensors
falls detection
toileting algorithm
Additional relevant MeSH terms:
Fecal Incontinence
Delirium
Urinary Incontinence
Enuresis
Frailty

Study Results

No Results Posted as of Aug 7, 2020