Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford
Oxford, Oxfordshire, OX3 9DU, United Kingdom
NCT Number: NCT06560931
Every year more than 700,000 women give birth in the United Kingdom. Of these at least 8700 nearly die - called a "near-miss", and 70 die. Many more women suffer harm, often with effects lasting for life. Women from less wealthy areas and particular ethnic groups are more likely to come to harm.
"Vital signs" include measurements of blood pressure, heart and breathing rates. Doctors and midwives use tools that score vital signs to spot women becoming unwell. These tools are called "Modified Obstetric Early Warning Scores" (MOEWS). Despite their use, poor outcomes still occur. This may be because MOEWS use only the most recent vital signs. Using extra data like blood tests may help spot unwell people earlier.
The study aims to reduce poor outcomes for women giving birth. The study will find better ways of describing, spotting, and treating women becoming unwell.
The study have planned four linked projects to develop an electronic advanced maternal obstetric early warning system (eMOEWS). Patient and Public (PPIE) collaborators have developed this work with CI's. The study work closely with them throughout this project.
Once the study has completed these four projects, they plan to carry out a trial to assess whether the new eMOEWS leads to better outcomes than the existing tools.
This study is active but is not currently recruiting participants.
Notify Me16 year and older
Female
Observational
Oxford, Oxfordshire, OX3 9DU, United Kingdom
Every year more than 700,000 women give birth in the United Kingdom. Of these at least 8700 nearly die - called a "near-miss", and 70 die. Many more women suffer harm, often with effects lasting for life. Women from less wealthy areas and particular ethnic groups are more likely to come to harm.
"Vital signs" include measurements of blood pressure, heart and breathing rates. Doctors and midwives use tools that score vital signs to spot women becoming unwell. These tools are called "Modified Obstetric Early Warning Scores" (MOEWS). Despite their use, poor outcomes still occur. This may be because MOEWS use only the most recent vital signs. Using extra data like blood tests may help spot unwell people earlier.
The study aims to reduce poor outcomes for women giving birth. The study will find better ways of describing, spotting, and treating women becoming unwell.
The study has planned four linked projects to develop an electronic advanced maternal obstetric early warning system (eMOEWS). Patient and Public (PPIE) collaborators have developed this work with the CI's. The study will work closely with them throughout this project.
Once the study have completed these four projects, they plan to carry out a trial to assess whether the new eMOEWS leads to better outcomes than the existing tools. This trial will be described in a separate protocol.
Project One The study will develop new definitions of worsening illness in women giving birth. They will work with the PPIE colleagues and other experts, reviewing published work. This will help staff use routinely collected health data to spot early illness, before a woman becomes very unwell. The study will check that the new definitions reliably identify women becoming unwell.
Project Two Using the new definitions, the study will test how well current MOEWS pick up worsening illness. The study will use data from eight to twelve NHS maternity units serving diverse women, and our national maternal review programme.
Project Three The study will develop an advanced, electronic MOEWS (eMOEWS) working with our PPIE collaborators and other experts. This will use extra information known to affect the risk of poor outcomes. The study will test how well the eMOEWS spots worsening illness, using our new definitions.
Project Four The study will develop a way to digitally display eMOEWS on maternity units. The study will work with staff who use computers along with experts in NHS computer systems. This will allow staff to understand quickly which women are at risk, and why. The study will design guidelines for how to use eMOEWS on maternity units with women and staff. This will make sure our new system helps give women the right care at the right time.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Patient data collection:
Inclusion criteria
Exclusion criteria
Staff:
Inclusion criteria
Exclusion criteria
Time frame: During pregnancy or in the immediate postpartum period.
Predictive performance of new early warning scores, assessed by: discrimination, calibration, and clinical utility.
Time frame: During pregnancy or in the immediate postpartum period.
'Near-miss' and 'pre-near-miss' outcome criteria measurable using routinely available electronic data, assessed in NHS hospitals
Time frame: During pregnancy or in the immediate postpartum period.
Descriptive statistics to describe whether the electronic criteria used correctly identified the conditions.
Descriptive statistics of missed and captured events according to electronic criteria Descriptive comparison to published rates
Time frame: 05/2029
Cohort developed and ready for assessment
Time frame: 05/2029
Evidence-based assessment of existing MOEWS, both in new retrospective (assessed by discrimination, risk of our key events at each MOEWS/MEWS level) and nationally recognised mortality/morbidity (assessed by sensitivity and duration of prior warning) cohorts
Time frame: 05/2029
Relative performance of new MOEWS, best published MOEWS and NHSI national MOEWS for prediction of near-miss or pre-near-miss
Time frame: 05/2029
Relative performance assessment of eMOEWS, new validated vital-signs-based MOEWS, best published MOEWS and NHSI national MOEWS for prediction of 'near-miss' or 'pre-near-miss'
Time frame: 05/2029
User co-designed eMOEWS implemented within 4 NHS sites. System Usability Scale performance
Time frame: 05/2029
Escalation and response pathways protocolised iterated and tested in a simulated environment
University of Oxford
Other
Defining, Recognising and Escalating Maternal Early Deterioration (DREaMED): Decreasing Inequality Through Improved Outcomes.
Acronym: DREaMED
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