Would Artificial Intelligence Reduce Delays to Nurse Response Times (WAiRD)

Would Artifical Intelligence Reduce Delays to Nurse Response Times

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.

Study Overview

• Status: Recruiting
• Conditions: Nurse's Role
• Intervention / Treatment: Device: novel nurse call system

• Study Type: Observational
• Enrollment (Estimated): 40

Contacts and Locations

• Study Contact: Name: Lucy Leese; Phone Number: 0113 2065455; Email: l.leese@nhs.net
• Study Contact Backup: Name: Sarah Hall; Phone Number: 0113 2065455; Email: leedsth-tr.researchgovernance@nhs.net

Study Locations

• United Kingdom
  • Leeds, United Kingdom, LS9 7TF
    • Recruiting
    • Leeds Teaching Hospital NHS Trust
    • Contact: Muzahir Tayebjee; Phone Number: 01132066051; Email: muzahir.tayebjee@nhs.net

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: N/A

• Sampling Method: Non-Probability Sample

Study Population

All patients admitted to the cardiology ward

Description

Inclusion Criteria:

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

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

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Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
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; 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.
Bed bay B; Time from nurse call system activated by standard system to initial response timeT1 and time to complete task T2.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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.	1 year

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Nursing time saved	The time taken using the novel system will be measured against the regular method to find the difference in time.	1 year
patient acceptability of the novel system	this is a qualitative measure	1 year

Collaborators and Investigators

• Sponsor: The Leeds Teaching Hospitals NHS Trust

Study record dates

Study Major Dates

• Study Start (Actual): May 23, 2023
• Primary Completion (Estimated): September 2, 2024
• Study Completion (Estimated): September 2, 2024

Study Registration Dates

• First Submitted: September 5, 2023
• First Submitted That Met QC Criteria: September 12, 2023
• First Posted (Actual): September 21, 2023

Study Record Updates

• Last Update Posted (Actual): October 27, 2023
• Last Update Submitted That Met QC Criteria: October 26, 2023
• Last Verified: October 1, 2023

More Information

Terms related to this study

• Other Study ID Numbers: CD22/153868

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No