Suchergebnisse

ObjectivesThe Family Nurse Partnership (FNP) is a specialist home-visiting programme for first-time teenage mothers. Developed in the US, short-term outcomes (by age 2 years) were established in England in the Building Blocks trial. We used routine data (health, education, social care) linked to our trial cohort to assess longer-term impact.
ApproachMothers recruited to the trial and their first-born children were linked to health (Hospital Episode Statistics/HES: NHS Digital; Abortion statistics: Department of Health and Social Care), education/social care (National Pupil Database/NPD: Department for Education) data in England up to age 7-years. Analysis of data within in a trusted-research environment assessed programme impact upon child maltreatment, child development/educational and maternal life course outcomes when compared to usually provided health and social care support alone. Our primary outcome was child in need registration. Planned sub-group analysis included differential effects by maternal age, deprivation level, care experience and for child outcomes, sex.
ResultsMatch rates for 1547 children were 97.4% (NPD) and 98.3% (HES). We found no difference between trial arms in proportion of children assessed as in need (adjusted odds ratio (aOR) OR:0.98, 95% confidence interval (CI): 0.74 to 1.31). Aside from a longer duration in care for children in the usual care arm (two months), there were no other differences in maltreatment outcomes. Children in the FNP arm were more likely to achieve a good level of development at reception age at age 4-5 years (aOR:1.24, 95%CI: 1.01 to 1.52) and, after adjusting for month of birth, to reach the expected standard in reading at Key Stage 1 at age around 7 years (aOR:1.26, 95%CI: 1.02 to 1.57).
ConclusionsWe found programme improvements for child development/educational achievement but not for child maltreatment outcomes. Additional sub-group analysis revealed some evidence of the programme benefiting mothers with greater baseline vulnerability and boys, consistent with previous trials. The study benefits from the linkage of administrative data to a previously randomised trial cohort.

BackgroundAnalysis of routine data makes an important contribution to service evaluation and research, providing cost-efficiencies, objective outcomes, burden reduction for patient and the public and is promoted by both policy and funders. Organisational, legal and ethical governance provide a framework for research but there is an onus on researchers to maintain their awareness of good practice when working with routine data.
Aim To co-produce with data provider, researcher and public stakeholders a training curriculum for researchers working with routine data.
Methods A curriculum for online and face-to-face training will be developed through consultations with three stakeholder groups. The first are researchers with existing interest /experience of using routine data. An online survey will be disseminated via UK research networks encompassing a range of disciplines and sectors. The non-probabilistic survey addresses current challenges, training experiences and learning preferences. Focus groups with three UK data provider organisations (SAIL, NHS Digital, National Pupil Database) will address provider's experience of working with researchers, any training or support they either require, provide or sign-post to and opportunities to support best practice. Thirdly, a facilitated public consultation exercise using a deliberative enquiry process will be undertaken as a day's workshop and include lay contributors identified via the HealthWise Wales cohort.
ResultsWe will present initial results from each stakeholder engagement activity and show how this has informed the draft training curriculum and our understanding of potential benefits that the training will deliver.
ConclusionsThe public may remain largely unaware of data captured when using public services, how it may contribute to research and the protections that apply. Involving the public in the development of researcher training informs this process and enables researchers to more effectively engage with patients and participants. Training will be promoted through data provider and research networks across sectors in the UK.

IntroductionWhile public engagement activity in healthcare may include a focus on uses of patient data, use of social care/ education data may be relatively overlooked. The public may be less aware about how their social care data may be used. Some concepts such as benefits and risks may also differ.
Objectives and ApproachOur objective is to co-produce with members of the public a package of materials that researchers may then use to promote public understanding of and engagement in research that uses routine data from health and social care settings.
We are running workshops with two groups of young families (teenage mothers, some of whom have received specialist home-visiting support) to explore key concepts and messages about routine data use, including sensitive data such as maltreatment and regulatory child protection interventions. The workshop includes completing a story board for an animated video. This will be co-produced by the same young people.
ResultsOur recent work with young families has shown a preference for visual based methods over text-based approaches to explain routine data linkage. This represents a key opportunity for innovation. We have explored how members of the public understand and make sense of routine data from various settings (health/social care) and its use in research. Working with a professional animator, the co-production of a prototype animation aims to engage members of the public about the nature, benefits and safeguards of using routine public records in health and social care research. The presentation will summarise the method of co-production, review the prototype animation and associated materials for researchers ('toolkit'). Finally, we will recap key messages identified from the workshops that underpin the animation and other dissemination plans.
Conclusion/ImplicationsOur existing understanding of public views (e.g. from consumer panels) may not represent well perspectives from population groups, such as teenage parents. Working with young families who may otherwise rarely engage in such work provides their unique perspectives, adding richness to our understanding of public views on routine data usage.

ObjectivesDomiciliary care workers (DCWs) continued to provide social care to vulnerable adults in their own homes throughout the COVID-19 pandemic. However, evidence of pandemic impact upon DCWs' health is mixed. The OSCAR study aimed to quantify the impact of COVID-19 upon health outcomes of DCWs in Wales, and explore causes of variation.
ApproachData for all registered DCWs in Wales are newly available via the SAIL Databank using a secured, privacy-protecting encrypted anonymisation process. Occupational registration data for DCWs working during the pandemic was combined with electronic health records data to describe health outcomes within the first two years of the pandemic. Rates of confirmed COVID-19 infections and health outcomes including mental health contacts, fit notes, respiratory infections, and mortality will be reported and explore variation (by factors such as age, sex, ethnicity, deprivation quintile, employer). We will also explore changes over time (pre- and post- onset of COVID-19 pandemic) in outcomes.
ResultsThe OSCAR study used anonymised health records for 15,727 registered DCWs in Wales. PCR-confirmed infection rates in the first full year of the pandemic (March20-February21) were 12% although lower in males (9%) than for females (12%). However, 28% of care workers received care for mental health with large differences observed between males (20%) and females (29%), and between workers from different health board regions (range 22% to 33%). The extent to which these represent pre-pandemic rates overall and how they compare to the broader community will be explored in our remaining work. A qualitative sub-study involving interviews with DCWs has informed our approach to modelling and to interpretation of findings.
ConclusionUsing novel anonymised occupational records at a national level and existing linked EHR data and qualitative interviews, the OSCAR study will quantify the risk of COVID-19 on DCWs' health and explore sources of variation. This will provide a secure base for informing public health policy and occupational guidance.

BackgroundThe use of administrative data in health and social science research continues to expand, with increased availability of data and interest from funders. Researchers, however, continue to experience delays in access, storage and sharing of administrative data. Training opportunities are limited and typically specific to individual data providers or focussed on the analytical aspects of working with administrative data. The CENTRIC study was funded by the Information Commissioners Office, with the aim of developing a broader training curriculum for researchers working with administrative data in the UK.
MethodsA mixed-methods design informed curriculum content, including surveys with researchers, focus group discussions with data providers and workshops with members of the public. Researchers were identified from relevant administrative data networks and invited to participate in an online survey identifying training needs. Data providers were approached with a request to input to a face-to-face or online meeting with two members of the research team about their experiences of working with researchers. Data were analysed within the broad framework of the interview schedule, free text responses in the survey were analysed thematically.
Results107 researchers responded to the online survey and four data providers participated in the focus groups. We identified five main themes, relating to research training needs for UK researchers working with administrative data: communication; timelines; changes & amendments; future-proofing applications; and, the availability of training and support. Data providers either provided additional evidence on these learning needs or ways to address identified challenges. Six modules were developed addressing these training needs. Quotes from the survey and focus groups are used anonymously in the online training modules.
ConclusionThe CENTRIC online training curriculum was launched in September 2020 and is available, free of charge for UK researchers. CENTRIC specifically addresses commonly identified training needs of researchers working with administrative data.

ObjectivesThe Family Nurse Partnership (FNP) is an intensive home visiting service for teenage first-time mothers, developed/trialled in the US and adapted/trialled across Europe. The Scottish Government aims to build on and supplement the existing evidence base for FNP, to assess effectiveness of the programme, for future improvement work in Scotland.
ApproachThe commissioned natural experiment of FNP, takes advantage of existing information infrastructures in Scotland from health, education and social care and FNP programme implementation data. A cohort design was used covering ten Health Boards in Scotland. The cohort included first-time teenage mothers enrolled as FNP Clients between 2010 and 2016 and women who met FNP eligibility criteria but were pregnant when the programme was not recruiting (Controls). Outcomes are mapped to the Scottish FNP logic model and include those being tested statistically (n=34) or, where direction of effect is uncertain, outcomes are rare or data quality poor, descriptively (n=20).
ResultsWe established a model of data linkage to routine Scottish data. Approvals were obtained to access data on over 8000 mothers (FNP Clients and Controls) and their children which formed the study cohort and were mapped to routine health, education and social care data. Outcomes covered maternal (health (smoking, alcohol/drugs), subsequent pregnancies/births, education) and child (health, development, education, protection) domains. Observed baseline imbalances between study arms will be described and adjusted for in modelling. Results will be published by the time of the conference and include sensitivity analyses that explore a priori sub-groups, variation by health board, year of booking and programme dosage.
ConclusionThe impact of this evaluation will establish a robustly matched study cohort, develop the evidence base on FNP in Scotland and internationally, develop a more streamlined linkage and approval process, and identify outcomes for short-term follow-up and importantly for a longer-term follow-up of the mothers and their children.

IntroductionThe method used to define a GP-consultation using routine data will vary depending on the data source and research question. However, without consensus the approach will be tackled by numerous researchers and invariably result in different definitions. The LUCI study is assessing outcomes of childhood UTI using routine data sources.
Objectives and ApproachWe are interested in GP urine sampling rate and re-consultation rate. The GP dataset includes multiple clinical (acute, routine monitoring, prescribing, results) and administrative codes. A GP consultation therefore needed to be defined. GP read code frequencies for our study cohort of children were produced. One researcher reviewed the codes that represented 80% of the data and classified them as a consultation or not. Where there was uncertainty this was independently reviewed by two clinicians and discrepancies agreed by the management team.
ResultsWe will present the decisions and assumptions made for this study in defining a GP consultation. 25,623 Read Codes represented the consultations for our study cohort of which 460 codes represented 80% of the consultations. The remaining 20% of codes represented <0.032% of records each. The 460 Read Codes were reviewed and following independent review and agreement from the management group 149 Read Codes were excluded. These were grouped into the following categories Administrative (e.g. Incoming Mail Processing, Ethnicity codes), Vaccinations, Child Health (e.g. First Smiled), Asthma and Medication Review. The GP consultations to be included in the analysis were then restricted to exclude these codes. This has been an important step in cleaning and understanding the data prior to analysis.
Conclusion/ImplicationsA consultation was defined for this study however there will be pros and cons to this method. In lieu of a consensus approach to the method this work is the first step to sharing approaches to help researchers with the same challenge.

BackgroundPOOL is a cohort study designed to establish whether waterbirth, compared to leaving a pool prior to birth, is as safe for mothers and infants. It is a novel case study using routine maternity and neonatal data for research purposes, including the adaptation and addition of locally collected electronic data at sites.
AimWe aimed to establish the feasibility of the study design, which combines data from maternity information systems(MIS) and neonatal data using a dissent-based linkage model and the addition of new variables into the MIS.
MethodsThe study will utilise individual level data entered into local MIS at 30 NHS Trusts linked with the National Neonatal Research Database(NNRD). New variables were added to one pilot site before rolling out to the remaining sites. A third party added the new variables, extracted data from the MIS to send to the study team and transferred data for matching to the NNRD, ensuring the study team receive only anonymised data. The feasibility study aimed to establish the quality and completion of the newly added variables, the levels of missingness for key outcomes from an extract of 4 years of retrospective data, and ensured the datasets could link using the study ID generated by our third party.
ResultsThe new variables were added into the MIS and data were extracted after a 10week pilot. New variables were present and had been entered as per specified metadata requirements. 23,140 records were extracted from the retrospective data and key variables assessed for missingness e.g.place of birth(<0.1% missing). The datasets could link using the studyID generated by the third party.
ConclusionThrough study set-up and in this pilot, we provide evidence that the main study is feasible, satisfies governance requirements and likely to generate data of sufficient quality to address our main research questions.

IntroductionThe Family Nurse Partnership(FNP) is an intensive home-visiting service for teenage first-time mothers (and children), developed/trialled in the US and adapted/trialled across Europe.The Scottish Government(SG) aims to build on and supplement the existing national/international evidence base for FNP, to assess effectiveness and opportunities for optimisation of the programme, for future decision making in Scotland.
Objectives and ApproachThe evaluation commissioned is a natural experiment of FNP, taking advantage of the existing information infrastructure in Scotland. This natural experiment represents an important opportunity to determine programme impact upon many key programme outcomes using routinely collected data at a lower cost than a comparably sized effectiveness trial. Key objectives are: to identify clients in receipt of FNP-support and a control sample of matched families who would meet criteria for FNP but did not receive support, to obtain approval and through anonymised data linkage link to health and other data, and to determine the effect of FNP across a range of maternal and child outcomes.
ResultsThe succes of the natural experiment design in trying to replicate the gold standard design of the RCT will be presented and will cover the following topics: (how cases and a comparable group of first-time teenage women have been identified across 10 Health Boards (HBs) between 2009 and 2016 using data made available by the electronic Data Research and Innovation Service (eDRIS) from FNP, NHS Scotland and SG; the matching process of the cases and controls using propensity score methods to ensure an unbiased comparison; the linkage to health, social care and educational datasets and the approval processes involved, and the strengths and limitations of using routine data to evaluate relevant study outcomes that map to a logic model.
Conclusion/ImplicationsThe impact of this evaluation into the effectiveness of FNP in Scotland will establish a robustly matched study cohort, a more strealmined linkage and approval process, and identification of outcomes not only for a short-term follow-up but also for a longer-term follow-up of the teenage mothers and their children.

ObjectivesThe Department for Education funded local authorities (LAs) in England to embed social workers into schools (SWIS) so that they can work more effectively with teachers, children and families. A two-arm cluster randomised-controlled trial is evaluating the effect of SWIS compared to schools without on referrals to Children's Social Care.
ApproachLAs collate information about all children who are referred to Children's Social Care within their authority. A case report form has been developed by the trial team to collect school-level information on child protection enquiries, referrals, child in need assessments and numbers of days children spent in state care. Cost data are also included for an economic evaluation. LAs return a completed dataset each quarter, reporting aggregate numbers by school and year group. Data on attendance and attainment will be requested separately from the National Pupil Database (NPD) in 2023.
ResultsQuarterly (n=6) data was supplied for 291 schools across 21 LAs. We will focus on this method of data collection and its challenges and opportunities. Relying on 21 external parties to provide all trial data in a timely manner brought risks to the collation of trial outcome data but has reduced the overall costs of data collection. LAs work with a number of different (and changing) IT systems, many of which are not compatible with each other. This, along with personnel changes in data teams, has led to delays. Receiving aggregate data limits the amount of quality control possible, therefore detailed guidance mitigated potential data input errors. Working with LAs to develop and refine these guidance materials at the outset paid dividends.
ConclusionUsing routine LA data is a novel cost-efficient approach to collecting trial outcome data at scale. However, the disjointed and varying data architecture that exists in LAs presents practical challenges. This means we relied on good working relationships with the LAs, including regular communication and collaborative problem solving.

IntroductionResearchers are increasingly using routinely collected data in addition to, or instead of, other data collection methods. The UK government continues to invest in research centres to encourage use of these data, and trials and cohort studies utilise data linkage methods in the follow-up of participants. This does not come without its limitations and challenges, such as data access delays.
ObjectiveThis paper outlines the challenges faced by three projects utilising individual-level routinely-collected linked data for the longer-term follow-up of participants.
MethodsThese studies are varied in design, study population and data providers. One researcher was common to the three studies and collated relevant study correspondence, formal documentary evidence such as data sharing agreements and, where relevant, meeting records to review. Key themes were identified and reviewed by other members of the research teams. Mitigating strategies were identified and discussed with a data provider representative and a broader group of researchers to finalise the recommendations presented.
ResultsThe challenges discussed are grouped into five themes: Data application process; Project timelines; Dependencies and considerations related to consent; Information Governance; Contractual. In presenting our results descriptively we summarise each case study, identify the main cross-cutting themes and consider the potential for mitigation of challenges.
ConclusionsWe make recommendations that identify responsibilities for both researchers and data providers for mitigating and managing data access challenges. A continued conversation within the research community and with data providers is needed to continue to enable researchers to access and utilise the wealth of routinely-collected data available. The suggestions made in this paper will help researchers be better prepared to deal with the challenges of applying for data from multiple data providers.

Introduction"Big data" – including linked administrative data – can be exploited to evaluate interventions for maternal and child health, providing time- and cost-effective alternatives to randomised controlled trials. However, using these data to evaluate population-level interventions can be challenging.
ObjectivesWe aimed to inform future evaluations of complex interventions by describing sources of bias, lessons learned, and suggestions for improvements, based on two observational studies using linked administrative data from health, education and social care sectors to evaluate the Family Nurse Partnership (FNP) in England and Scotland.
MethodsWe first considered how different sources of potential bias within the administrative data could affect results of the evaluations. We explored how each study design addressed these sources of bias using maternal confounders captured in the data. We then determined what additional information could be captured at each step of the complex intervention to enable analysts to minimise bias and maximise comparability between intervention and usual care groups, so that any observed differences can be attributed to the intervention.
ResultsLessons learned include the need for i) detailed data on intervention activity (dates/geography) and usual care; ii) improved information on data linkage quality to accurately characterise control groups; iii) more efficient provision of linked data to ensure timeliness of results; iv) better measurement of confounding characteristics affecting who is eligible, approached and enrolled.
ConclusionsLinked administrative data are a valuable resource for evaluations of the FNP national programme and other complex population-level interventions. However, information on local programme delivery and usual care are required to account for biases that characterise those who receive the intervention, and to inform understanding of mechanisms of effect. National, ongoing, robust evaluations of complex public health evaluations would be more achievable if programme implementation was integrated with improved national and local data collection, and robust quasi-experimental designs.

Introduction: Individual, social and economic circumstances faced by young mothers can challenge a successful start in life for their children. Intervening early might enhance life chances for both mother and child. The Family Nurse Partnership (FNP) is an intensive nurse-led home visiting programme developed in the US which aims to improve prenatal health behaviours, birth outcomes, child development and health outcomes, and maternal life course. Establishing evidence of effectiveness beyond the original US setting is important to understand where further adaptation is required within a country specific context.
Objective: This study will form one strand of the Scottish Governments' plan to evaluate the effectiveness of FNP as compared to usual care for mothers and their children in Scotland and will focus only on outcomes that can be identified using routine administrative data systems.
Methods: This study is a natural experiment with a case-cohort design using linked anonymised routine health, educational and social care data. Cases will be women enrolled as FNP Clients in ten NHS Health Boards in Scotland and Controls will be women who met FNP eligibility criteria but were pregnant at a time when the programme was not recruiting. Outcomes are mapped to the Scottish FNP logic model. All comparative analyses will be pre-specified, conducted on an intention to treat basis and will use multilevel regression models to compare outcomes between groups.
Discussion: The study protocol is based upon the specification of FNP commissioned by the Scottish Government. This study design is novel for the evaluation of the FNP/NFP programmes which are primarily evaluated with an RCT. Outcomes included within the study have been selected on the basis that they are outcomes FNP aims to influence and where there is routine data available to assess the outcome.

This project was funded by the Scottish Government Children and Families Directorate [project reference CASE/290185]. ; Peer reviewed ; Publisher PDF

BackgroundUsing routinely collected clinical data for observational research is an increasingly important method for data collection, especially when rare outcomes are being explored. The POOL study was commissioned to evaluate the safety of waterbirth in the UK using routine maternity and neonatal clinical data. This paper describes the design, rationale, set-up and pilot for this data linkage study using bespoke methods.
MethodsClinical maternity information systems hold many data items of value for research purposes, but often lack specific data items required for individual studies. This study used the novel method of amending an existing clinical maternity database for the purpose of collecting additional research data fields. In combination with the extraction of existing data fields, this maximised the potential use of existing routinely collected clinical data for research purposes, whilst reducing NHS staff data collection burden.
Wellbeing Software® provider of the Euroking® Maternity Information System, added new study specific data fields to their information system, extracted data from participating NHS sites and transferred data for matching with the National Neonatal Research Database to ascertain outcomes for babies admitted to neonatal units. Study set-up processes were put in place for all sites. The data extraction, linkage and cleaning processes were piloted with one pre-selected NHS site.
ResultsTwenty-six NHS sites were set-up over 27 months (January 2019 - April 2021). Twenty-four thousand maternity records were extracted from the one NHS site, pertaining to the period January 2015 to March 2019. Data field completeness for maternal and neonatal primary outcomes were mostly acceptable. Neonatal identifiers flowed to the National Neonatal Research Database for successful matching and linkage between maternity and neonatal unit records.
DiscussionPiloting the data extraction and linkage highlighted the need for additional governance arrangements, training at NHS sites and new processes for the study team to ensure data quality and confidentiality are upheld during the study. Amending existing NHS electronic information systems and accessing clinical data at scale, is possible, but continues to be a time consuming and a technically challenging exercise.