Critical IllnessSEISMIC-RNCT05917574
A Study to Evaluate the Introduction of New Staffing Models in Intensive Care: a Realist Evaluation (SEISMIC-R)
An observational study of Critical Illness and Staff Attitude, run by University of Hertfordshire at 1 site in United Kingdom.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Critical Illness, Staff Attitude, Organisation
- What is being tested?
- n/a (non-interventional)
- How many people
- 87 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 14 Jun 2023to 30 Sep 2025
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Staff population: Workstream 1 and Workstream 2 sample is expected to be 294 (assuming 100% ICUs respond) plus 30 interviews and 30 ethnographic observation participants Critical care patients population (de-identified data, no individual consent/sampling needed, using routine aggregated dataset): Workstream 3/4 the data set is likely to exceed 29300 Intensive care admissions
Who may be able to join
- 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.
- 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.
Show all 9Show fewer
- 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.
Who cannot join
- -
Trial locations and contacts
1 site in 1 country.
United Kingdom1 site
East and North Hertfordshire NHS Trust, Lister Hospital
Stevenage
About this study
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.
Read more
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:
- 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)
- 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.
- 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.
Read the detailed description
Background: Optimising deployment of the scarce nursing workforce in the intensive care unit (ICU) is paramount for patient safety, and staff wellbeing. ICU staffing models are determined by National Health Service (NHS) service specification, with 1:1 patient to registered nurse (RN) ratios for the highest acuity patients. A rapid expansion of ICU capacity during COVID19 led to adoption of alternative models, using more support staff, non-ICU qualified nurses and other professionals, reaching up to 70% at surge. The strengths, weaknesses, costs and effects of these models, and benefits of retaining them, remain uncertain. Lower nurse-staffing levels, and high workload, have been associated with adverse outcomes for patients, staff and organisations although ICU-specific evidence is limited. Studies focus on levels of RNs, contributing little to understanding consequences of changes retained post-COVID, or to guiding adoption of alternative staffing models. It is unclear how changes in staffing or specific models affect various outcomes.
Aim: To identify the key components of an optimal nurse staffing model for deployment in ICU.
Objectives/Methods: Guided by a realist framework, the investigators propose to interlink workstreams (WS) over 2 years to allow cross-fertilisation of ideas/hypotheses and inform emerging programme theories.
- To identify and describe organisation of models, exploring intended mechanisms and outcomes for how different models work, the investigators will conduct:
- a UK survey (WS 1) of all 294 ICUs in England/Wales/Northern Ireland (NI)/Scotland that will identify staffing models emerging/retained since COVID19, compared with United Kingdom (UK) service specifications.
- a realist evaluation (WS 2, cross-cutting workstream) and detailed case studies involving six sites, and 30-40 interviews with: nurses/senior nurses; organisational leads; critical care network managers/commissioners; families/patients, to test emerging programme theories. Rapid ethnographies (n=30), will elucidate how staffing decisions are made.
- To provide estimates of variability in demand for nursing staff and estimate associations between staffing patterns and patient outcomes, the investigators will:
- use administrative e-roster (nurse staffing roster) data and patient data (WS 3) from the Intensive Care National Audit and Research Centre Case Mix Programme (2019-2023) to assess whether and how patient/staff outcomes vary with differing staff models between units/case study sites.
- To develop simulation models to show the impact of models on capacity, cost and patient flow, the investigators will use simulation modelling (WS 4) to explore scenarios for different staffing policies given case mixes of case study units, swiftly and with no patient impact.
Analysis: Data integration occurs across all workstreams in WS 5. Theories developed from WS2 case studies will be further tested against WS 3 observational data and inform WS 4 mathematical simulation models of ICU capacity, patient outcomes and patient flow, to inform emerging propositions for the realist evaluation programme theories as context-mechanism-outcome configurations.
- Conditions
- Critical Illness, Staff Attitude, Organisation, Intensive Care
- Being tested
- n/a (non-interventional)
- Keywords
- Staffing, Patient outcomes, intensive care, critical care, healthcare organisation, nurse, realist evaluation
- Medical subject headings
- Critical Illness
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
n/a (non-interventional)Other
Non-interventional (Realist Evaluation study)
What is being measured
The primary outcome is the main question the study is designed to answer.
Death from all causes within 30 days of ICU admission
Mortality
Measured: 2019-2023
Secondary outcomes (6)
Discounted Quality-adjusted Life Year (QALYs)
Quality-adjusted Life Years (QALYs)
Measured: 2019-2023
Composite death/discharge to long term-care (LTC)
Death/discharge to LTC
Measured: 2019-2023
ICU-acquired infection
ICU-acquired infection
Measured: 2019-2023
Days of organ support in ICU
Days of organ support in ICU (per organ)
Measured: 2019-2023
Cost of ICU stay
Cost of ICU and post-ICU stay (in hospital)
Measured: 2019-2023
Staff absence
Sickness and absence (and associated costs)
Measured: 2019-2023
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Jun 2023
- Study start14 Jun 2023
- Primary completion30 Sep 2025
- Study completion30 Sep 2025
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Critical IllnessStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Other
- Enrolment
- 87 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Hertfordshire
- Sponsor type
- University, hospital or other
- Collaborators
- University of Southampton, Imperial College Healthcare NHS Trust, Intensive Care National Audit & Research Centre, University of Exeter, University of Plymouth, London South Bank University
- Responsible party
- Sponsor
- Investigators
- Natalie A Pattison, Principal investigator, University of Hertfordshire
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05917574
- Sponsor's protocol ID
- UH:02990
- Acronym
- SEISMIC-R
- Status last verified
- Apr 2026
- First submitted
- 4 May 2023
- Last updated
- 4 May 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: We have a data sharing management plan available on request
Publications
Hadley R, Dogan B, Wood N, Bohnacker N, Mouncey PR, Pattison N; SEISMIC-R investigator group. National survey evaluating the introduction of new and alternative staffing models in intensive care (SEISMIC-R) in the UK. BMJ Open. 2025 Apr 10;15(4):e088233. doi: 10.1136/bmjopen-2024-088233.
PubMed 40216433
Study at a glance
From the registry record, last updated by the sponsor on 4 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Study to Evaluate the Introduction of New Staffing Models in Intensive Care: a Realist Evaluation (SEISMIC-R)
- ClinicalTrials.gov ID
- NCT05917574
- Acronym / sponsor ID
- SEISMIC-R / UH:02990
- Conditions
- Critical Illness, Staff Attitude, Organisation, Intensive Care
- Keywords
- Staffing, Patient outcomes, intensive care, critical care, healthcare organisation, nurse, realist evaluation
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 87 participants (actual)
- Lead sponsor
- University of HertfordshireUniversity, hospital or other
- Collaborators
- University of Southampton, Imperial College Healthcare NHS Trust, Intensive Care National Audit & Research Centre, University of Exeter, University of Plymouth, London South Bank University
- Study start
- 14 Jun 2023 (actual)
- Primary completion
- 30 Sep 2025 (actual)
- Study completion
- 30 Sep 2025 (actual)
- First posted
- 26 Jun 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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:
- 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)
- 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.
- 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.
Detailed description
Background: Optimising deployment of the scarce nursing workforce in the intensive care unit (ICU) is paramount for patient safety, and staff wellbeing. ICU staffing models are determined by National Health Service (NHS) service specification, with 1:1 patient to registered nurse (RN) ratios for the highest acuity patients. A rapid expansion of ICU capacity during COVID19 led to adoption of alternative models, using more support staff, non-ICU qualified nurses and other professionals, reaching up to 70% at surge. The strengths, weaknesses, costs and effects of these models, and benefits of retaining them, remain uncertain. Lower nurse-staffing levels, and high workload, have been associated with adverse outcomes for patients, staff and organisations although ICU-specific evidence is limited. Studies focus on levels of RNs, contributing little to understanding consequences of changes retained post-COVID, or to guiding adoption of alternative staffing models. It is unclear how changes in staffing or specific models affect various outcomes.
Aim: To identify the key components of an optimal nurse staffing model for deployment in ICU.
Objectives/Methods: Guided by a realist framework, the investigators propose to interlink workstreams (WS) over 2 years to allow cross-fertilisation of ideas/hypotheses and inform emerging programme theories.
- To identify and describe organisation of models, exploring intended mechanisms and outcomes for how different models work, the investigators will conduct:
- a UK survey (WS 1) of all 294 ICUs in England/Wales/Northern Ireland (NI)/Scotland that will identify staffing models emerging/retained since COVID19, compared with United Kingdom (UK) service specifications.
- a realist evaluation (WS 2, cross-cutting workstream) and detailed case studies involving six sites, and 30-40 interviews with: nurses/senior nurses; organisational leads; critical care network managers/commissioners; families/patients, to test emerging programme theories. Rapid ethnographies (n=30), will elucidate how staffing decisions are made.
- To provide estimates of variability in demand for nursing staff and estimate associations between staffing patterns and patient outcomes, the investigators will:
- use administrative e-roster (nurse staffing roster) data and patient data (WS 3) from the Intensive Care National Audit and Research Centre Case Mix Programme (2019-2023) to assess whether and how patient/staff outcomes vary with differing staff models between units/case study sites.
- To develop simulation models to show the impact of models on capacity, cost and patient flow, the investigators will use simulation modelling (WS 4) to explore scenarios for different staffing policies given case mixes of case study units, swiftly and with no patient impact.
Analysis: Data integration occurs across all workstreams in WS 5. Theories developed from WS2 case studies will be further tested against WS 3 observational data and inform WS 4 mathematical simulation models of ICU capacity, patient outcomes and patient flow, to inform emerging propositions for the realist evaluation programme theories as context-mechanism-outcome configurations.
Study design
- Observational model
- Other
- Time perspective
- Other
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Staff population: Workstream 1 and Workstream 2 sample is expected to be 294 (assuming 100% ICUs respond) plus 30 interviews and 30 ethnographic observation participants Critical care patients population (de-identified data, no individual consent/sampling needed, using routine aggregated dataset): Workstream 3/4 the data set is likely to exceed 29300 Intensive care admissions
Key inclusion criteria (9 listed)
- 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.
- Patient or family member over 18 years old.
Key exclusion criteria (1 listed)
- -
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| n/a (non-interventional)Non-interventional (Realist Evaluation study) | Other | – |
Primary outcome
Death from all causes within 30 days of ICU admission
Time frame: 2019-2023
Mortality
6 secondary outcomes
Discounted Quality-adjusted Life Year (QALYs)
Time frame: 2019-2023
Composite death/discharge to long term-care (LTC)
Time frame: 2019-2023
ICU-acquired infection
Time frame: 2019-2023
Days of organ support in ICU
Time frame: 2019-2023
Cost of ICU stay
Time frame: 2019-2023
Staff absence
Time frame: 2019-2023
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 May 2026.
- Derived from this study: PubMed 40216433Hadley R, Dogan B, Wood N, Bohnacker N, Mouncey PR, Pattison N; SEISMIC-R investigator group. National survey evaluating the introduction of new and alternative staffing models in intensive care (SEISMIC-R) in the UK. BMJ Open. 2025 Apr 10;15(4):e088233. doi: 10.1136/bmjopen-2024-088233.
- Individual participant dataSharing planned: No. We have a data sharing management plan available on request
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Natalie A Pattison principal investigator
University of Hertfordshire
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Critical Illness and Staff Attitude, run by University of Hertfordshire at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 9 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 4 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Death from all causes within 30 days of ICU admission (time frame: 2019-2023). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05917574, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 4 May 2026.