Understanding the health needs of mothers involved in family court cases

Text removed is struck through; text added is underlined. Unchanged paragraphs are summarised rather than repeated.

Objective for processing

University College London (UCL) are proposing to link an existing cohort of mothers and babies (held by the research team under a separate Data Sharing Agreement (DSA) with UCL; NIC-393510-D6H1D) with programme information from the Children and Family Court Advisory and Support Service (Cafcass). Women aged between 15 and 50 years, with at least one live birth recorded in the Hospital Episodes Database between 01/04/1997 and 31/03/2017 will make up the cohort. It is estimated that there will be a maximum of 12 million women in this cohort. This cohort of women will be linked to Cafcass data on women involved in care proceedings between 01/04/2007 and 31/03/2019, which includes 113,191 mothers. Those women who are not linked to Cafcass data will act as a control cohort for analysis. This will allow UCL to compare women linked in the Cafcass data to the general population of women giving birth as 97% of women in England who give birth in NHS hospitals. University College London (UCL) requires access to NHS England data for the purpose of the following research project: ‘Understanding the health needs of mothers involved in family court cases’. The Cafcass extract used for this study will be minimised by the UCL research team to only contain information on women aged 15-50 years who were party to section 31 applications (care proceedings where local authorities apply to have a child removed from parental supervision due to serious concerns for the child safety and wellbeing). The extract will contain demographic information on the mothers (date of birth, local authority of residence), information on the children subject to the case (number of children, month and year of birth, sex), and information on the care proceedings (hearing dates, final legal output). Women who were aged between 15 and 50 years when their first live birth occurred recorded in the Hospital Episodes Database between 01/04/1997 and 01/04/2017 will make up the cohort. It is estimated that there will be a maximum of 12 million women in this cohort. This cohort of women will be linked with programme information from the Children and Family Court Advisory and Support Service (Cafcass) which relates to women involved in care proceedings between 01/04/2007 and 31/03/2022, and which includes around 113,000 mothers. UCL will be receiving up-to-date information about care proceedings for the same cohort of women for the years 2022 and 2023. The Cafcass data is held by the Children and Family Court Advisory and Support Service, and available for researchers upon request. (Research must be approved by the Cafcass Research Advisory Committee. The committee checks if the proposed research is feasible, as well as beneficial for Cafcass and for children and families using the service. The research will only be approved if it is relevant to Cafcass’ statutory remit and strategic aims. In this case, the committee has approved the UCL project as being done in accordance with CJCSA section 13 and falling within its strategic aims). The women identified from HES records whose records cannot be linked with Cafcass data will act as a control cohort for analysis. This allows UCL to compare women linked in the Cafcass data to the general population of women giving birth as 97% of women in England who give birth in NHS hospitals. The data under NIC-393510-D6H1D is disseminated for a programme of research within the healthcare provision theme of the Policy Research Unit for Children, Young People and Families (CPRU), within University College London (UCL) which is funded by the Department of Health and Social Care (DHSC). The extract of data from NIC-393510-D6H1D for the purpose of this agreement NIC-196253 will only contain HES APC, A&E, Outpatient data and Civil Registration data on women who had a record of a live birth between the ages of 15 and 50 years old between 1 April 1997 and 31 March 2017. The Cafcass extract used for this study will be minimised by the UCL research team to only contain information on women aged 15-50 years who were party to section 31 applications. Section 31 of the Children Act 1989 pertains to care proceedings where local authorities apply to have a child removed from parental supervision due to serious concerns for the child safety and wellbeing. The extract will contain demographic information on the mothers (date of birth, local authority of residence), information on the children subject to the case (number of children, month and year of birth, sex), and information on the care proceedings (hearing dates, final legal output). This request aims to assess the feasibility of using linked health and family court administrative data sets to facilitate research to explore the underlying issues such as long-term health and mental problems. Further, it aims to inform policy about associations between justice system risk factors, such as regional variation in returns to court and health outcomes such as time to next pregnancy, mental health exacerbations during court proceedings. The Cafcass data is held by the Children and Family Court Advisory and Support Service, and available for researchers upon request. (Research must be approved by the Cafcass Research Advisory Committee. The committee checks if the proposed research is feasible, as well as beneficial for Cafcass and for children and families using the service. The research will only be approved if it is relevant to Cafcass’ statutory remit and strategic aims. In this case, the committee has approved the UCL project as being done in accordance with Criminal Justice and Court Services Act 2000 (CJCSA) section 13 and falling within its strategic aims). The aim of this use of the data is to assess the feasibility of using linked health and family court administrative data sets to facilitate research to explore the underlying issues such as long-term health and mental problems. Further, it aims to inform policy about associations between justice system risk factors, such as regional variation in returns to court and health outcomes such as time to next pregnancy, mental health exacerbations during court proceedings. [3 paragraphs unchanged] Question 2: Among mothers involved with care proceedings, what characteristics are associated with time to subsequent pregnancy, adversity related admissions and adverse outcomes related to court ? court? [5 paragraphs unchanged] UCL will explore risk factors known at live birth (such as maternal [67 words unchanged] using women’s medical history as recorded in Hospital Episode Statistics (HES) (e.g. long-term long term conditions or adversity-related admissions as recorded in ICD-10 or OPCS codes (classification [25 words unchanged] onwards, as well as to identify any long-term conditions in the mothers. The purpose of this application falls under Article 6 (1) (e) of the GDPR and the lawful basis for using information collected routinely for administrative purposes for research is the ‘public task’. This is part of the University’s commitment to ‘integrate research and innovation for the long-term benefit of humanity’. The application also falls under Article 9 (2) (j), as scientific research. The following NHS England data will be accessed: The study has been designed by UCL researchers without the involvement of the funders (Nuffield Foundation). • Hospital Episode Statistics Outpatients (HES OP) There are no alternative, less intrusive ways of achieving the purpose of this study. • Hospital Episode Statistics Admitted Patient Care (HES APC) UCL are the sole data controller who also process the data under this agreement. • Hospital Episode Statistics Accident & Emergency (HEA A&E) There are no other organisation involved in the study other than those referenced. • HES: Civil Registration (Deaths) bridge • Civil Registrations of Death - Secondary Care Cut Access to these datasets is necessary to asses risk factors and outcomes in mothers subject to care proceedings. The Cafcass extract used for this study will be minimised by the UCL research team to only contain information on women aged 15-50 years who were party to section 31 applications (care proceedings where local authorities apply to have a child removed from parental supervision due to serious concerns for the child safety and wellbeing). The extract will contain demographic information on the mothers (date of birth, local authority of residence), information on the children subject to the case (number of children, month and year of birth, sex), and information on the care proceedings (hearing dates, final legal output). The Cafcass data is held by the Children and Family Court Advisory and Support Service, and available for researchers upon request. (Research must be approved by the Cafcass Research Advisory Committee. The committee checks if the proposed research is feasible, as well as beneficial for Cafcass and for children and families using the service. The research will only be approved if it is relevant to Cafcass' statutory remit and strategic aims. In this case, the committee has approved the UCL project as being done in accordance with CJCSA section 13 and falling within its strategic aims). The level of the data will be: • Pseudonymised Identifiable data was processed for the previous iteration of this DSA (v0.11), this was necessary to enable linkage of the data with data from Cafcass. There will no new data linkage taking place as a part of this DSA, therefore no further processing or flow of identifiable data will take place under this DSA. The data will be minimised as follows. • Limited to a study cohort of women who had a live birth while between the ages of 15 and 50 years old between the period from 1 April 1997 to 1 April 2017 • Limited to data between 01/04/1997 and 31/03/2023 - data will be obtained by UCL under a separate DSA (ref: DARS- NIC-393510-D6H1D). UCL will access HES APC, A&E, HES OP data and Civil Registration (deaths) records for the study cohort described above. UCL is the research sponsor and the controller as the organisation responsible for ensuring that the data will only be processed for the purpose described above. The lawful basis for processing personal data under the UK GDPR is: Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller; The lawful basis for processing special category data under the UK GDPR is: Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject. It is in the public interest because the research influences Department of Health policy makers, service providers, healthcare professionals and the general public. This directly benefits the health of mothers involved in care proceedings and the healthcare provided to mothers at risk of care proceedings in the here and now and this is key to reducing future burden on the NHS and social care services. The funding is provided by the Nuffield Foundation. The funding is specifically for the project described. The funder will have no ability to suppress or otherwise limit the publication of findings. Amazon Web Services (AWS) is a processor acting under the instructions of UCL. AWS’ role is limited to secure back-up of data stored in UCL’s Data Safe Haven. UCL uses offsite data centre services provided by VIRTUS data centre. VIRTUS does not have access to the data. Data will be accessed by PhD students affiliated with UCL. Any student working with the Data held under this DSA must have completed relevant data protection and confidentiality training and are subject to UCL’s policies on data protection and confidentiality. Any students accessing the Data will do so under the supervision of a substantive employee of UCL. UCL would be responsible and liable for any work carried out by students. These students would only work on the Data for the purposes described in this DSA. Previous public and patient engagement work for this data linkage project has helped to identify further stakeholders to engage with this work. UCL will continue to undertake public and patient engagement work to support interpretation of findings and to discuss methods of sharing study findings to ensure findings are accessible to both policy, practitioners and the study population. The group strongly supported the collection of the data for the purposes described above.

Processing activities

Data sources As data linkage has been completed, no further data will flow to NHS England under this DSA. Previous data flows are described below for reference. The datasets to be linked are: Cafcass supplied NHS England with a list of identifier variables for women aged 15-50 years involved in section 31 care proceedings, including name (first and surname) date of birth, local authority of residence during care proceeding and postcode histories, alongside a study specific pseudo-identifier number (pseudo-study ID) for mothers involved in care proceedings in England that started between 1 April 2007 and 31 March 2022. Only identifiers for women aged 15 to 50 years involved in section 31 proceedings were transferred. No other Cafcass data will flow. The flow of identifying data from Cafcass to NHS England is Practice Direction 12G which enables Cafcass to lawfully share information about family court proceedings for the purposes of an approved research project. 1) Hospital Episode Statistics (HES APC, A&E and OPD) and death registration data which contains details of all hospital contacts and deaths in NHS hospitals in England collected from 1 April 1997 to date (data UCL already hold under NIC-393510-D6H1D). Women aged between 15 and 50 years, with at least one live birth recorded in the Hospital Episodes Database between 01/04/1997 and 31/03/2017 will be extracted to make up the cohort to be liked with the Cafcass data. These identifiers were linked to records held in the Master Patient Service (MPS). The identifiable information disclosed by Cafcass was used by NHS England to facilitate linkage with the MPS data in order to identify patients within the HES data. 2) The Children and Family Court Advisory and Support Service database (Cafcass) contains information on family care proceedings, including demographic information on persons involved in court applications (adults and children), hearing and application dates, and proceeding outcomes. Data is available from Cafcass from 2007 onwards. The Cafcass extract used for this study will be minimised to only contain information on women aged 15-50 years who were party to section 31 applications (care proceedings where local authorities apply to have a child removed from parental supervision due to serious concerns for the child safety and wellbeing). Cafcass will minimise the data in this way before it is sent to UCL. The extract will contain demographic information on the mothers (date of birth, local authority of residence), information on the children subject to the case (number of children, month and year of birth, sex), and information on the care proceedings (hearing dates, final legal output). A linked file was created, with the pseudo-study ID provided by Cafcass and the matching Token Person ID as recorded in MPS. The national data opt-out was then applied to this linked file and anyone from the Cafcass cohort who has opted out of having their data shared for research or planning purposes was removed from the linked file. The study cohort will include all women for whom a section 31 application has been made (by an English local authority) concerning their child(ren) between April 2007 and March 2019. Though most section 31 applications result in a section 31 order being made, a considerable number result in children being placed with extended family under private law orders (such as a Special Guardianship Order) and a small number of applications are dismissed or are subject to an ‘Order of No Order’. Each of these outcomes are equally as important, particularly when considering the heterogeneity of this study population with respect to identifying risk factors for returning to court for subsequent s31 court proceedings. NHS England disclosed a file of pseudonymised Token Person IDs for women within the Cafcass dataset to UCL to enable linkage with this existing HES-Civil Registrations extract for the purpose of this study. The NHS England file did not contain the NHS Number or the postcode. To mitigate the risk of re-identification, identifiers will be used by the trusted third party (NHS Digital) to carry out the link between the two data sets (Cafcass and HES, via PDS), the final analysis file will only contain pseudonymised non-sensitive variables. - NHS England transferred to UCL a list of pseudonymised study IDs for women who linked and encrypted Token Person IDs for women who link and women who do not link. Data flow: There will be no requirement or attempt to re-identify individuals. • Cafcass will supply NHS Digital with a list of identifier variables for women aged 15-50 years involved in section 31 care proceedings, including name (first and surname) date of birth, local authority of residence during care proceeding and postcode histories, alongside a study specific pseudo-identifier number (pseudo-study ID) for mothers involved in care proceedings in England that started between 1 April 2007 and 31 March 2017. Only identifiers for women aged 15 to 50 years involved in section 31 proceedings will be flowing. No other Cafcass data will flow. The flow of identifying data from Cafcass to NHS Digital is Practice Direction 12G which enables Cafcass to lawfully share information about family court proceedings for the purposes of an approved research project. The data will not be transferred to any other location. These identifiers will be linked to records held in the Patient Demographic Service (PDS) using an algorithm that prioritises the most recent postcode in Cafcass (at the end of the last case the woman was involved in). The identifiable information disclosed by Cafcass will be used by NHS Digital to facilitate linkage with the Personal Demographics Service (PDS) data in order to identify patients within the HES data. The data will be stored in the UCL Data Safe Haven (DSH). • For the remaining unmatched Cafcass records, the second postcode in Cafcass will then be compared with PDS as above. This approach will be repeated up to a maximum of 3 postcodes in Cafcass. (Only up to 3 postcodes per person are available from Cafcass for linkage but UCL would expect NHS Digital to compare these with up to 5 postcodes from the PDS). The UCL DSH uses Dual Factor Authentication to access and handle data transferred into the DSH service. This ensures that only the named applicants will have access to the data from DSH. Removing data from the Data Safe Haven is only allowed for the Principal Investigator. The DSH operates as a walled space and researchers are not able to connect to the internet or export data from it. • A linked file will be created, with the pseudo-study ID provided by Cafcass and the matching NHS number and postcode as recorded in PDS. Amazon Web Services provides cloud hosting services to UCL and will store the data as contracted by UCL. • The national data opt-out will then be applied to this linked file and anyone from the Cafcass cohort who has opted out of having their data shared for research or planning purposes will be removed from the linked file. UCL uses offsite data centre services provided by VIRTUS data centre. • UCL will use HES data from an existing data extract (NIC-393510-D6H1D) which is currently held by UCL to create a minimised extract containing HES APC, A&E, Outpatient data and Civil Registration data on only women who had a record of a live birth between the ages of 15 and 50 years old between 1 April 1997 and 31 March 2017. The data will be accessed by authorised personnel via remote access. The data will remain on the UCL Data Safe Haven at all times. NHS Digital will disclose a file of pseudonymised HES-IDs for women within the Cafcass dataset to UCL to enable linkage with this existing HES-Civil Registration extract for the purpose of this study. The NHS Digital file will not contain the NHS Number or the postcode. The data will not leave England at any time. • NHS Digital will retain the identifier file of all individuals linked in Cafcass-PDS and PDS-HES and all the postcodes used in linkage and postcode dates for 12 months to address data queries. This data set will not contain any attribute data and will be held separately from the final analysis file. Access is restricted to substantive employees of UCL or PhD students who have authorisation from the principal investigator. • NHSD will transfer to UCL a list of pseudonymised study IDs for women who link and encrypted HES-IDs for women who link and women who do not link. UCL will not link the Cafcass cohort linked to HES and Civil Registration data disseminated under the separate DSA (ref: DARS-NIC-393510-D6H1D) to any of the other datasets held under that separate DSA. There will no requirement or attempt to re-identify individuals. All personnel accessing the data have been appropriately trained in data protection and confidentiality. Data processing is only carried out by substantive employees of UCL who have been appropriately trained in data protection and confidentiality. The data requested will be kept in UCLs Data Safe Haven (DSH). A file transfer mechanism enables information to be transferred into the Safe Haven simply and securely. The data linkage has been completed under the original Agreement and no further data linkage will take place. The data linkage details are retained below for information purposes. The UCL DSH uses Dual Factor Authentication to access and handle data transferred into the DSH service. This ensures that only the named applicants will have access to the data from DSH. Removing data from the Data Safe Haven is only allowed for the Principle Investigator. The datasets that were linked are: UCL will not attempt to link the Cafcass cohort linked to HES and Civil Registration data disseminated under NIC-393510-D6H1D to any of the other datasets held under NIC-393510-D6H1D. 1) Hospital Episode Statistics (HES APC, A&E and OPD) and death registration data which contains details of all hospital contacts and deaths in NHS hospitals in England collected from 1 April 1997 to 31 March 2023 (data UCL already hold under NIC-393510-D6H1D). Women aged between 15 and 50 years, with at least one live birth recorded in the Hospital Episodes Database between 01/04/1997 and 01/04/2017 were extracted to make up the cohort to be liked with the Cafcass data. 2) The Children and Family Court Advisory and Support Service database (Cafcass) contains information on family care proceedings, including demographic information on persons involved in court applications (adults and children), hearing and application dates, and proceeding outcomes. Data is available from Cafcass from 2007 onwards. The study cohort includes all women for whom a section 31 application has been made (by an English local authority) concerning their child(ren) between April 2007 and March 2022. Though most section 31 applications result in a section 31 order being made, a considerable number result in children being placed with extended family under private law orders (such as a Special Guardianship Order) and a small number of applications are dismissed or are subject to an Order of No Order. Each of these outcomes are equally as important, particularly when considering the heterogeneity of this study population with respect to identifying risk factors for returning to court for subsequent s31 court proceedings. To mitigate the risk of re-identification, identifiers were used by the trusted third party (NHS England) to carry out the link between the two data sets (Cafcass and HES, via MPS), the final analysis files only contains pseudonymised non-sensitive variables. There will be no requirement and no attempt to reidentify individuals when using the data. Researchers from UCL will analyse the data for the purposes described below. [2 paragraphs unchanged] • As a first step, UCL will determine the proportion of mothers in [28 words unchanged] violence, chronic conditions, or young age (<20 years) at (previous) live birth). • UCL will determine the frequency of hospital contacts (planned and unplanned) for [70 words unchanged] women are at risk of exacerbation's such as self-harm admissions during proceedings). From previous research as part of the Children Policy Research Unit (NIC-393510) Unit, UCL will have information on the sub-cohort of mothers with history of [19 words unchanged] whole population, for instance the rates and ages at first live birth. • The main analyses for question 1 will determine whether there are specific [56 words unchanged] (e.g. at antenatal care, or during hospitalisation prior to pregnancy or birth). • In secondary analyses, UCL will determine whether associations between healthcare risk factors [49 words unchanged] or treatment for mental health problems, which might improve capacity to parent. • UCL will use multiple regression techniques to study these associations. This will [16 words unchanged] for risk factors such as area-based deprivation levels and underlying health needs. [1 paragraph unchanged] • Two key outcomes for question 2 are the timing of subsequent pregnancies [33 words unchanged] but it is not currently known how many women have subsequent pregnancies. • UCL will also analyse a range of secondary outcomes obtained from the [10 words unchanged] death. Assessing these outcomes will allow UCL to examine how indicators of healthcare need are associated with the primary outcome ʹtiming of subsequent pregnancies and care proceedings. Findings from these analyses will inform inferences about whether input from healthcare might help prevent further care proceedings. • UCL will use multivariable survival analyses to determine time to next pregnancy [102 words unchanged] be used to identify mothers most likely to experience further care proceedings. • The analyses will quantify the relative contribution of health events and healthcare [44 words unchanged] potential for healthcare interventions to reduce the risk of subsequent care proceedings. [3 paragraphs unchanged] No new data will flow to UCL (University College London) for the [19 words unchanged] UCL are not requesting any additional data on hospitalisations, A&E attendances, outpatient appoints, appointments, or civil registrations to flow between NHS Digital England and UCL. UCL under this agreement. UCL requires data on the whole-population (i.e. all women with a live [57 words unchanged] and local population characteristics vary considerably across England, as well as by time (i.e. 2007 to 2019). time. Understanding differences by area and time are crucial to ensuring any study finding are generalisable and relevant to both national and local policy makers and service planners. For some analyses UCL must use statistical matching methods to match mothers [47 words unchanged] etc). The variables used in matching, as well as the timing for ‘baseline’ baseline measurements, will vary by analyses dependent on the study outcome. In order [34 words unchanged] admissions) UCL require a sufficient number of controls to robustly model outcomes. The proposed control group would not result in any additional data flowing between NHS Digital England and UCL, and a lack of a whole-population control group would impact [23 words unchanged] inform policy and practice at the local as well as national level.

Expected output

The research will inform Department of Health and Social Care and Ministry of Justice policy makers, service providers and practitioners about patient and service factors associated with the health needs of mothers and children involved in care proceedings in family court. UCL will work with the funder, the Nuffield Foundation to organise a symposium inviting key policy makers and scientists to showcase the findings. The expected outputs of the processing will be: Additionally, UCL will share results with patients who are part of a mental health service user group based at King’s College London and PAUSE, a charity working with women who have experienced, or are at risk of, repeat removals of children from their care. https://www.pause.org.uk/about-us/ • A report of findings to the Nuffield Foundation at the end of the project with an overview of the research findings. UCL has also formed a project advisory group that includes six leading practitioners from across health, family justice and child safeguarding. Part of UCL’s planned discussions with this group will include identifying ways to improve communication about this project and to identify a wide range of organisations including within health, children’s social care, family justice and the voluntary sector with which to share study findings. This group includes a PAUSE practice lead and the programme manager for SHRINE (a human rights -based service in South London delivering sexual and reproductive healthcare to marginalised populations including people with serious mental illness or substance misuse). • Submissions to peer reviewed journals such as the International Journal of Population Data Science, Lancet Public Health or Archives of Disease in Childhood in 2024 and 2025. Previous public and patient engagement work for this data linkage project has helped to identify further stakeholders to engage with this work. UCL will continue to undertake public and patient engagement work to support interpretation of findings and to discuss methods of sharing study findings to ensure findings are accessible to both policy, practitioners and the study population. • Presentations to the Ministry of Justice Areas of Research Interest (ARI) academic seminar series, Cafcass analytical team, Nuffield Foundation The findings will be published in peer reviewed journals and reports prepared for the funder, the Nuffield Foundation. • Presentations at appropriate conferences such as the, International Population Data Linkage Conference, International Society for the Prevention of Child Abuse and Neglect, Royal College of Paediatrics and Child Health annual conference, and Informatics for Health conference The papers resulting from these studies will be published in peer-reviewed journals (such as the Lancet, Archives of Disease in Childhood, PLoS Medicine, BMJ Open) and presented at scientific conferences (such as the, International Population Data Linkage Conference, International Society for the Prevention of Child Abuse and Neglect, Royal College of Paediatrics and Child Health annual conference, and Informatics for Health conference). The outputs will not contain NHS England data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived. UCL aim to present the work at scientific conferences during 2021 and use feedback provided at these meetings to write up papers to be submitted for publication in 2021. The outputs will be communicated to relevant recipients through the following dissemination channels: Outputs will be aggregated with small numbers suppressed in line with the HES analysis guide. • Journals • Public reports • Press/media engagement

Expected measurable benefits

The research will inform Department of Health and Social Care and Ministry of Justice policy makers, service providers and practitioners about patient and service factors associated with the health needs of mothers and children involved in care proceedings in family court. UCL will work with the funder, the Nuffield Foundation to organise a symposium inviting key policy makers and scientists to showcase the findings. UCL has also formed a project advisory group that includes six leading practitioners from across health, family justice and child safeguarding. Part of UCL’s planned discussions with this group will include identifying ways to improve communication about this project and to identify a wide range of organisations including within health, children’s social care, family justice and the voluntary sector with which to share study findings. This group includes a PAUSE practice lead and the programme manager for SHRINE (a human rights -based service in South London delivering sexual and reproductive healthcare to marginalised populations including people with serious mental illness or substance misuse). The use of the data could: • help the system to better understand the health and care needs of populations. • advance understanding of regional and national trends in health and social care needs. • support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work). [8 paragraphs unchanged] It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients. UCL will share results with patients who are part of a mental health service user group based at King’s College London and PAUSE, a charity working with women who have experienced, or are at risk of, repeat removals of children from their care. https://www.pause.org.uk/about-us/

Benefits reported

Yielded Benefits is not a requirement for new applications. The data linkage was only recently completed, benefits are expected to be yielded from 2024 onwards.