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RecruitingNCT06043986WAiRDUpdated Oct 27, 2023

Would Artificial Intelligence Reduce Delays to Nurse Response Times

An observational study in Nurse's Role, sponsored by The Leeds Teaching Hospitals NHS Trust. Recruiting at 1 site in United Kingdom. Open to participants aged 18 Years to 100 Years. Per ClinicalTrials.gov, last updated 2023-10-27.

Sponsored by The Leeds Teaching Hospitals NHS Trust · Observational

From the registry’s dates

  • Primary completion was expected by Sep 2024, 2 years 1 month ago, but the record still lists the study as recruiting.
  • Started May 2023; still recruiting 3 years 4 months later.
Study type
Observational
Model
Other
Time perspective
Other
Enrollment
40
Ages
18 Years to 100 Years
Sex
All
01

Study summary

Patients are admitted to wards at all times of day and night and in various states of ill health. As this research is non interventional and does not impact on patient safety, the guidance from the ethics committee was reviewed and agreed that it would be appropriate to enrol every admission into the 2 bed bays and gain consent within 24 hours of admission.All data collected within the trial using the smart tablets will be associated to a study number, no patient details will be stored on the smart tablet and therefore the cloud data store.It has been discussed with the trust information governance and this complies with their regulations.

Any patient identifiable data will be kept by the research team. All data will be archived and stored as per the Sponsors policy. The novel nurse call system has been designed to be user friendly to all patients regardless of age, learning ability and first language used. By using colours, images and words in the hope that this will be accessible to all. The nursing staff on the ward advised on the main reasons for the nurse call system activation and therefore the icons used in the novel system were adapted from this. This trial was discussed in the patient and public involvement group. As this is a pilot trial, any adaptions that need to be made will be made before the large scale trial.

02

Conditions studied

  • Nurse's Role
03

In context

Lead sponsor

The Leeds Teaching Hospitals NHS Trust is the lead sponsor of 95 studies on the registry; 15 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 100 Years
Sexes eligible
All
Sampling method
Non-probability sample

Study population

All patients admitted to the cardiology ward

Eligibility criteria

Inclusion Criteria:

All adults 18 years who are admitted to the cardiology admissions ward will be eligible to take part.

-

Exclusion Criteria: Any patient who does not wish to participate will have their anonymised data removed from the trial.

-

05

Study design

Observational model
Other
Time perspective
Other
Enrollment
40 participants (estimated)
Patient registry
No

Groups and cohorts

  • Bed bay A

    Time from nurse call system activated by the novel nurse call system to initial response time T1 and time to complete task T2. Reason for nurse call system activated: Toilet/Pain/Medication/ /Need a nurse/Other

    Device: novel nurse call system

  • Bed bay B

    Time from nurse call system activated by standard system to initial response timeT1 and time to complete task T2.

Interventions

  • Devicenovel nurse call system

    Inavya Ventures Ltd (Inavya) has developed a medical-grade artificial intelligence enabled mobile system (AVATR) to support out-of-hospital healthcare. AVATR is approved as a UK Government official supplier of healthcare technology on the UK Digital Marketplace for cloud-based solutions (G Cloud). AVATR in hospital, will connect to the existing AVATR outpatient service building on existing AVATR technology, which is regulated CE-mark Grade 1 (EU/UK). The research team will create, deploy and test a novel ward-based AI technology innovation to transform current nurse call systems to patient-centred mobile technology assets at bedside, thus reducing the need for unproductive visits by nurses to the bedside, which takes away time and attention where it is otherwise best served. Having mobile connection to the patients, would improve patient experience and saving nursing staff time, thereby improving quality of care, and saving money.

06

What researchers measure

Primary outcomes

  1. study objective

    The primary outcome of this study is the time taken to respond to the alert raised by the novel nurse call system and time taken from call to completion of task.

    Time frame: 1 year

Secondary outcomes

  1. Nursing time saved

    The time taken using the novel system will be measured against the regular method to find the difference in time.

    Time frame: 1 year

  2. patient acceptability of the novel system

    this is a qualitative measure

    Time frame: 1 year

07

Study locations

1 of 1 sites recruiting
  • Leeds Teaching Hospital NHS Trust
    Leeds, LS9 7TF, United Kingdom
    Recruiting
08

References and documents

Individual participant data

Plan to share: No

No publications or documents are linked to this record.

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Oct 27, 2023, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT06043986
Lead sponsor
The Leeds Teaching Hospitals NHS Trust
Responsible party
Sponsor
First posted
Sep 21, 2023
Start date
May 23, 2023
Primary completion
Sep 2, 2024 (estimated)
Completion
Sep 2, 2024 (estimated)
Last update
Oct 27, 2023

Study contacts

Lucy Leese
Contact
l.leese@nhs.net
0113 2065455
Sarah Hall
Contact
leedsth-tr.researchgovernance@nhs.net
0113 2065455

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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