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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.

ObjectivesWe describe the challenges and lessons learned from two studies using linked administrative data from health, education and social care sectors to evaluate the Family Nurse Partnership (FNP), an intervention supporting adolescent mothers in England(E) and Scotland(S). We present recommendations for studies using linked administrative data to evaluate complex interventions.
ApproachWe constructed two cohorts of all mothers aged 13-19 giving birth in NHS hospitals in England and Scotland between 2010-2016/17 using linkage of mothers and babies in hospital admissions data (E:Hospital Episode Statistics/S:Maternity Inpatient and Day Case), and identified FNP participation through linkage to FNP programme data. We additionally linked to health, educational and social care data for mothers and their babies (E:National Pupil Database/S:eDRIS). We used these data to identify key risk factors for enrolment in the FNP, assess the effect of the FNP on maternal and child outcomes, and determine programme characteristics modifying the effect of the FNP.
ResultsKey challenges: characterising the intervention and usual care, understanding quality of multi-sector data linkage, data access delays, constructing appropriate comparator groups and interpreting outcomes captured in administrative data. Lessons learned: evaluations require detailed data on intervention activity (dates/geography), and assessment of usual care, which are rarely readily available and are time-consuming to gather; data linkage quality is variable/not available, making defining denominators challenging; data access delays impeded on data analysis time; unmeasured confounders not captured in administrative data may prevent generation of an appropriate comparator group. Recommendations: Characteristics informing targeting should be explicitly documented, and could be enhanced using linked primary care data and information on household members (e.g. fathers). Process evaluation and qualitative research could help to provide better understanding of mechanisms of effect.
ConclusionLinkage of administrative data presents exciting opportunities for efficient evaluation of large-scale, complex public health interventions. However, sufficient information is needed on programme meta-data, targeting and important confounders in order to generate meaningful results. Study findings should help stimulate exploration with practitioners about how programmes can be improved.

The Brecon Group Register was established through pump-priming financial support provided by Novo Nordisk and subsequent funding from the Welsh Government. This study was funded by the Diabetes Research and Wellness Foundation (reference PP2017). The funders were not involved in the design of the study; the collection, analysis, and interpretation of data; writing the report; or the decision to submit the report for publication. ; Peer reviewed ; Publisher PDF

IntroductionDomiciliary care workers (DCWs) continued providing social care to adults in their own homes throughout the COVID-19 pandemic. Evidence of the impact of COVID-19 on health outcomes of DCWs is currently mixed, probably reflecting methodological limitations of existing studies. The risk of COVID-19 to workers providing care in people's homes remains unknown.
ObjectivesTo quantify the impact of COVID-19 upon health outcomes of DCWs in Wales, to explore causes of variation, and to extrapolate to the rest of the UK DCW population.
MethodsMixed methods design comprising cohort study of DCWs and exploratory qualitative interviews. Data for all registered DCWs in Wales is available via the SAIL Databank using a secured, privacy-protecting encrypted anonymisation process. Occupational registration data for DCWs working during the pandemic will be combined with EHR outcome data within the SAIL Databank including clinical codes that identify suspected and confirmed COVID-19 cases. We will report rates of suspected and confirmed COVID-19 infections and key health outcomes including mortality and explore variation (by factors such as age, sex, ethnicity, deprivation quintile, rurality, employer, comorbidities) using regression modelling, adjusting for clustering of outcome within Health Board, region and employer. A maximum variation sample of Welsh DCWs will be approached for qualitative interview using a strategy to include participants that vary across factors such as sex, age, ethnicity and employer. The interviews will inform the quantitative analysis modelling. We will generalise the quantitative findings to other UK nations.
DiscussionUsing anonymised linked occupational and 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.

Background Guidelines recommend the prompt diagnosis and treatment of UTI in young children to reduce the risk of renal scarring and possible long-term complications. However, the evidence for this association is weak and has been questioned. There is an urgent need to clarify this as the correct approach to urine sampling and diagnosis of UTI in children hinges on this association.
Main Aim Determine outcomes following UTI in childhood (<5years)
Approach We used the Secure Anonymised Information Linkage (SAIL) Databank to access demographic, hospital, GP and microbiology data from children in Wales. Children with >1 microbiologically confirmed UTI (mcUTI) aged <5, were compared to those with no mcUTI. The primary outcome was renal scarring and secondary outcomes included hypertension, chronic kidney disease and renal failure. The primary analysis used multinomial regression and time to event models.
Results A cohort of 159,201 children was defined. 11,099 (7.0%) had >1 mcUTI.
The overall prevalence of renal scarring in the cohort by age 7 was 0.16%; 1.26% in those with >1 mcUTI; 0.08% in those with no mcUTI. The unadjusted odds ratio (OR) was 16.62 (12.91-21.39) and adjusted 3.64 (2.57-5.14). Among the group with >1 mcUTI, predictors of renal scarring were VUR, younger age of first UTI, and greater number of UTIs <5
Conclusion UTI was associated with renal scarring even after adjusting for covariates.
The prevalence of renal scarring in children with >1 mcUTI was lower than expected. Possible explanations include poor coding in routine data, different patient populations or missed renal scarring diagnoses. We are currently validating our results using radiology data. If renal scarring diagnoses are being missed, a more proactive urine sampling and imaging strategy may be indicated. However, if renal scarring rates are low following UTI, this may not be necessary.

Funding This project has been funded by the Welsh Government through Health and Care Research Wales (project number 1068). Acknowledgments We acknowledge the support and input from Sarah Jones, our parent representative for the study. We are also grateful to the DUTY and EURICA participants for their agreement for continued use of their data for this study. The Centre for Trials Research receives funding from Health and Care Research Wales and Cancer Research UK. Wales Centre for Primary and Emergency Care Research (PRIME Centre Wales) receives funding from Health and Care Research Wales. The authors are supported by the Farr Institute CIPHER, funded by Arthritis Research UK, the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the Medical Research Council, the National Institute of Health Research, the National Institute for Social Care and Health Research (Welsh Assembly Government), the Chief Scientist Office (Scottish Government Health Directorates), and the Wellcome Trust (MRC grant number MR/K006525/1) and the National Centre for Population Health and Wellbeing Research (NCPHWR). Ethics approval Ethics approval of the study has been given by the Research Ethics Committee for Wales (16/WA/0166) and the transfer and use of identifiable data has been approved by the Health Research Authority's (HRA) Confidentiality Advisory Group (CAG) (16/CAG/0114). ; Peer reviewed ; Publisher PDF

BACKGROUND: It is estimated that around 160,000 households in Britain experience homelessness each year, although no definitive statistics exist. Between March and September 2020, as part of the initial 'Everyone In' government response to COVID-19 in England, 10,566 people were living in emergency accommodation and nearly 18,911 people had been moved into settled accommodation. However, some forms of temporary accommodation may not be suitable as shared facilities make it impossible for people to adhere to government guidelines to reduce the spread of COVID-19. METHODS: This is parallel group, pilot randomised controlled trial. The target is to recruit three local authorities, each of which will recruit 50 participants (thus a total of approximately 150 participants). Individuals are eligible if they are aged 18 and over, in a single-person homeless household, temporarily accommodated by the LA with recourse to public funds. Participants will be randomised to receive settled accommodation (intervention group) or temporary accommodation (control group). The intervention group includes settled housing such as Private Rented Sector (low and medium support), Social Housing (low and medium support), and Housing First (High support). The control group will maintain treatment as usual. The follow-up period will last 6 months. The primary outcome is to assess the feasibility of recruitment, retention, and acceptability of trial processes against progression criteria laid out in a traffic light system (green: all criteria are met, the trial should progress as designed in this pilot; amber: the majority of criteria are met and with adaptations to methods all criteria could be met; red: the minority of criteria are met and the pilot RCT should not proceed). Secondary outcomes include assessment of completeness of data collection at 3 and 6 months and percentage of participants consenting to data linkage, as well as a process evaluation and economic evaluation. DISCUSSION: This trial will address feasibility questions ...