CompletedNot Applicable

A Study to Evaluate the Introduction of New Staffing Models in Intensive Care: a Realist Evaluation (SEISMIC-R)

United Kingdom87 participantsStarted 2023-06-14

Plain-language summary

Background: Staffing in intensive care units (ICU) has been in the spotlight since the pandemic. Having enough nurses to deliver safe, quality care in ICU is important. However, what the skill mix should be (how many should be qualified nurses or have an ICU qualification) is unclear. Very little research has been done to look at which nursing staff combinations and mix of skills works best in ICU to support patients (described as 'staffing models').Research shows that there is a link between the quality of nurse staffing and poor patient outcomes, including deaths. Aim: Our research plans to look at different staffing models across the UK. This study aims to examine new staffing models in ICU across six very different Trusts. This study will use a research technique called Realist Evaluation that examines what works best in different situations and help to understand why some things work for some people and not others. The design of this approach will help to better understand the use of different staff ratios across different ICU settings. This study will examine what combinations of staff numbers and skills result in better patient care and improved survival rates. The aim is to produce a template that every ICU unit can use. To do this, this study will compare staffing levels with how well patients recover, and seek to understand the decisions behind staffing combinations. Methods: This study will: 1. carry out a national survey to understand the different staff models being used, comparing this against the current national standard (n=294 ICUs in the UK including Scotland) 2. observe how people at work in 6 hospitals (called ethnography), watching how they make decisions around staffing and the effect on patients. The investigators will also conduct interviews (30 interviews plus 30 ethnographic observations) to understand staffing decisions. 3. look at ICU staffing patterns and models, and linked patient outcomes (such as whether people survive ICU) over 3 years (2019-2023) in those hospitals, including with a very different combination of staffing). The investigators will then carry out some mathematical calculations to understand the best possible staffing combinations, and how this varies.

Who can participate

Age range18 Years

SexALL

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Inclusion Criteria: Interviews with nursing staff * Registered Nurses who have worked in ICU for at least six months. Inclusion criteria: Interviews with nurse managers * Clinically-based nurse managers who have worked in ICU for at least one year. Inclusion criteria: Interviews with organisational leads * Organisational leads who have been working in their role and in the ICU field for at least one year. Inclusion criteria: Interviews with regional managers/commissioners • Regional managers/commissioners who have been working in their role and in the ICU field for at least one year. Inclusion criteria: Interviews with patients/families * Patient or family member over 18 years old. * Patients who have been in General ICU for at least 48 hours in the last 6 months. * Family members who have visited ICU for at least 20 mins on two days in the preceding 6 months. * Patient discharged from hospital at least 2 weeks prior to the interview. * Patient expected to be well enough, after hospital discharge, to attend the interview and to have capacity to consent. Exclusion Criteria: \-

What they're measuring

Death from all causes within 30 days of ICU admission

Timeframe: 2019-2023

Trial details

NCT IDNCT05917574

SponsorUniversity of Hertfordshire

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2025-09-30