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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.
Full description
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.
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Patient data collection:
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Exclusion Criteria:
• Patients who have requested that their data not be used for research (e.g., NHS Opt-out).
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Inclusion criteria
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• Staff who do not consent
459,160 participants in 7 patient groups
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Data sourced from clinicaltrials.gov
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