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Data-Driven staffing: could algorithms determine nurse numbers?

NCT ID NCT06923943

Knowledge-focused Sponsor: University of Southampton Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing This study
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study looks at whether information already collected by hospitals can be used to predict how many nurses are needed on each ward. Researchers will analyze data from hospital systems and ask nurses for their input on staffing tools. The goal is to improve staffing decisions and patient care.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 80 people

The number the study aims to enrol. It can still change while the study runs.

Started

Nov 2025

Expected to finish

Jul 2026

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

English NHS acute hospital Trusts

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

National survey Inclusion Criteria: * safe staffing lead/nurse with responsibility for safe staffing or CNIO/nurse with responsibility for IT/electronic records Workshops Inclusion Criteria: * nursing manager with safe staffing remit/IT remit. OR * clinical nurse with experience of completing Safer Nursing Care Tool ratings. OR * NHS IT manager with familiarity of hospital Trust's systems for storing patient data. OR * representative of company who provide rostering or patient information system services to hospitals.

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As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Nursing workload

Contacts and locations

Locations

  • University of Southampton

    Southampton, United Kingdom

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