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Would Artificial Intelligence Reduce Delays to Nurse Response Times

Would Artifical Intelligence Reduce Delays to Nurse Response Times

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06043986
Acronym
WAiRD
Enrollment
40
Registered
2023-09-21
Start date
2023-05-23
Completion date
2024-09-02
Last updated
2023-10-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Nurse's Role

Brief 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.

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.

Sponsors

The Leeds Teaching Hospitals NHS Trust
Lead SponsorOTHER

Study design

Observational model
OTHER
Time perspective
OTHER

Eligibility

Sex/Gender
ALL
Age
18 Years to 100 Years

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. \-

Design outcomes

Primary

MeasureTime frameDescription
study objective1 yearThe 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.

Secondary

MeasureTime frameDescription
Nursing time saved1 yearThe time taken using the novel system will be measured against the regular method to find the difference in time.
patient acceptability of the novel system1 yearthis is a qualitative measure

Countries

United Kingdom

Contacts

Primary ContactLucy Leese
l.leese@nhs.net0113 2065455
Backup ContactSarah Hall
leedsth-tr.researchgovernance@nhs.net0113 2065455

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026