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| Name | Class |
|---|---|
| NHS England | OTHER_GOV |
| Guy's and St Thomas' NHS Foundation Trust | OTHER |
| King's College London | OTHER |
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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.
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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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Retrospective cohort | This study consists of a programme of work that is centred around a UK-based, multi-centre cohort study of women who are pregnant or have recently been pregnant. The study will use retrospective data from three representative collaborator NHS hospitals (who will form part of the retrospective cohort). | ||
| Prospective cohort | This study consists of a programme of work that is centred around a UK-based, multi-centre cohort study of women who are pregnant or have recently been pregnant. | ||
| MBRRACE-UK cohort | The study will use data from MBRRACE-UK, reviewing deaths, near-miss and pre-near-miss cases to estimate identification performance using the new definitions. | ||
| Patient interviews (escalation pathway) | This study consists of a programme of work that is centred around a UK-based, multi-centre cohort study of women who are pregnant or have recently been pregnant. All women in the cohort are likely to have had one of the near-miss or pre-near-miss events (as defined in WS1) or death. | ||
| Staff interviews/focus groups (escalation pathway) | Staff members will be involved in focus groups, interviews and testing the eMOEWS user interface. Inclusion criteria
|
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| Measure | Description | Time Frame |
|---|---|---|
| To develop, and validate an electronically-embedded, data-enhanced Maternal Early Warning Score (eMOEWS) with clinical escalation pathways | Predictive performance of new early warning scores, assessed by: discrimination, calibration, and clinical utility. | During pregnancy or in the immediate postpartum period. |
| Measure | Description | Time Frame |
|---|---|---|
| To define 'near-miss' and 'pre-near-miss' criteria for use with routinely-collected data to measure maternal outcomes | 'Near-miss' and 'pre-near-miss' outcome criteria measurable using routinely available electronic data, assessed in NHS hospitals | During pregnancy or in the immediate postpartum period. |
| To assess performance of the new near-miss and pre-near-miss outcome criteria in 3 hospitals and MBRRACE-UK. |
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Patient data collection:
Inclusion Criteria:
Exclusion Criteria:
• Patients who have requested that their data not be used for research (e.g., NHS Opt-out).
Staff:
Inclusion criteria
Exclusion criteria
• Staff who do not consent
All women aged 16 or over who are pregnant
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Patient retrospective and prospective data: All women who are treated by maternity services at study sites.
MBRRACE-UK cohort: All cases of maternal death and morbidity (for the cohorts described above) collected by MBRRACE-UK Patient interviews/Focus groups(escalation pathway): Women and their partners who have experienced near-miss events or other maternal complications.
Staff interviews/focus groups (escalation pathway and eMOEWS interface development): Staff members will be involved in focus groups, interviews and testing the eMOEWS user interface.
Staff training (simulation scenarios): Staff will also take part in scenario simulations (MOET).
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| Name | Affiliation | Role |
|---|---|---|
| Peter Watkinson | University of Oxford | Principal Investigator |
| Marian Knight | University of Oxford | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Critical Care Research Group, Nuffield Department of Clinical Neurosciences, University of Oxford | Oxford | Oxfordshire | OX3 9DU | United Kingdom |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot | Yes | No | No | Study Protocol | Jun 3, 2024 | Aug 9, 2024 | Prot_000.pdf |
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| ID | Term |
|---|---|
| D011248 | Pregnancy Complications |
| ID | Term |
|---|---|
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
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| Staff interviews/focus groups (eMOEWS interface development) | Staff members will be involved in focus groups, interviews and testing the eMOEWS user interface. Inclusion criteria
|
| Staff training (simulation scenarios) | Staff will also take part in scenario simulations (MOET). Inclusion criteria
|
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 |
| During pregnancy or in the immediate postpartum period. |
| To develop a large representative eight to twelve maternity unit cohort for model development and assessment | Cohort developed and ready for assessment | 05/2029 |
| To investigate the performance of existing MOEWS/MEWS in the new maternity cohort and in women who have died or had a near-miss or pre-near-miss event in pregnancy | 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 | 05/2029 |
| To develop and validate an optimal vital-signs-only-based MOEWS | Relative performance of new MOEWS, best published MOEWS and NHSI national MOEWS for prediction of near-miss or pre-near-miss | 05/2029 |
| To develop and validate an eMOEWS to improve detection in comparison to existing MOEWS/MEWS | 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' | 05/2029 |
| To design and deliver an eMOEWS interface | User co-designed eMOEWS implemented within 4 NHS sites. System Usability Scale performance | 05/2029 |
| To develop treatment escalation pathways | Escalation and response pathways protocolised iterated and tested in a simulated environment | 05/2029 |