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

Prinicipal Investigator: Professor Natalie Pattison, University Of Hertfordshire

Team: Professor Peter Griffiths, Dr Chiara Dall'Ora, Dr Christina Saville, Dr Lisa Whiting, Dr Melanie Handley, Dr Susie Pearce, Dr Marion Penn, Dr Paul Mouncey, Professor Thomas Monks, Mrs Clare Leon-Villapalos, Professor Suzanne Bench, Professor Ruth Endacott, Mr Jeremy Dearling, Mrs Jennifer Gordon.

University of Southampton, University of Hertforshire, University of Plymouth, Intensive Care National Audit & Research Centre, University of Exeter, Imperial College Healthcare NHS Trust, Guys & St Thomas' NHS Foundation Trust/London South Bank University, NIHR Clinical Research Network.

Start Date: 01 May 2023

End Date: 31 August 2024


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. There is national guidance, re-issued in April 2021, on how many nurses should care for ICU patients. 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’).


Across ICUs in UK, various ratios of qualified and unqualified nursing staff are being tried (staff ratios refer to the number of nurses caring for a set number of patients). Hospitals vary; some use a high proportion of non-registered nurses and others a low proportion of ICU qualified nurses. 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. We aim to examine new staffing models in ICU across six very different Trusts. We will use a research technique called Realist Evaluation that examines what works best in different situations and helps us to understand why some things work for some people and not others. The design of this approach will help us to better understand the use of different staff ratios across different ICU settings.


We will examine what combinations of staff numbers and skills result in better patient care and improved survival rates. Our aim is to produce a template that every ICU unit can use. To do this, we will compare staffing levels with how well patients recover, and seek to understand the decisions behind staffing combinations.

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