ObjectiveLinkage of longitudinal administrative data for mothers and babies supports research and service evaluation in several populations around the world. We established a linked mother-baby cohort using pseudonymised, population-level data for England.Design and SettingRetrospective linkage study using electronic hospital records of mothers and babies admitted to NHS hospitals in England, captured in Hospital Episode Statistics between April 2001 and March 2013.ResultsOf 672,955 baby records in 2012/13, 280,470 (42%) linked deterministically to a maternal record using hospital, GP practice, maternal age, birthweight, gestation, birth order and sex. A further 380,164 (56%) records linked using probabilistic methods incorporating additional variables that could differ between mother/baby records (admission dates, ethnicity, 3/4-character postcode district) or that include missing values (delivery variables). The false-match rate was estimated at 0.15% using synthetic data. Data quality improved over time: for 2001/02, 91% of baby records were linked (holding the estimated false-match rate at 0.15%). The linked cohort was representative of national distributions of gender, gestation, birth weight and maternal age, and captured approximately 97% of births in England.ConclusionProbabilistic linkage of maternal and baby healthcare characteristics offers an efficient way to enrich maternity data, improve data quality, and create longitudinal cohorts for research and service evaluation. This approach could be extended to linkage of other datasets that have non-disclosive characteristics in common.

When a patient or service user is treated or cared for, information is collected which supports their treatment. This information is also useful to commissioners and providers of NHS-funded care for 'secondary' purposes - purposes other than direct or 'primary' clinical care - such as:

• Healthcare planning
• Commissioning of services
• National Tariff reimbursement
• Development of national policy

SUS is a secure data warehouse that stores this patient-level information in line with national standards and applies complex derivations which support national tariff policy and secondary analysis.

Access to SUS is managed using Role-Based Access Control (RBAC) which grants appropriate access levels to identifiable, anonymised or pseudonymised data based on the users job role.

The dataset includes both patient level demographic, and inpatient data. It includes data on diagnosis, admission type and department for each episode of care for the patients.

Investment in the earliest stages of life is increasingly recognised to improve health across the life-course, beginning with the health of parents before pregnancy, in embryonic life, through to infancy, childhood, and into adulthood. eLIXIR BiSL combines information from routine maternity and neonatal health records and blood samples at two acute NHS Trust hospitals, along with mental health and primary care data. The study is able to address relationships between maternal and child physical health, and to investigate interactions with mental health. Participants are predominantly residents of South London, in areas with high levels of deprivation and ethnic diversity.

The BiSL data-linkage project uses opt-out consent to collect routine maternity and neonatal clinical patient data (GSTT and KCH NHS Trusts), mental health data from the SLaM CRIS platform, and primary care data from the LDN platform, for those registered with a GP in Lambeth. We hold the approval to also link with emergency and admissions data (HES), national fertility data (HFEA), and immunisation records (NIMS), as well as expanding primary care data to other boroughs in South London, namely: Southwark, Lewisham, and Bromley; the process to link these new data sources is currently ongoing.

At present, eLIXIR holds over 50,000 records. All records are deidentified, including masking of identifying information in open-text fields and use of pseudonymised identifiers. The data refresh process occurs every 6 months, and each update includes all retrospective data since conception of the cohort (October 2018), thus building a dynamic cohort.

The BiSL team includes members King’s College London Faculty of Life Sciences and Medicine and the Institute of Psychiatry, Psychology and Neurosciences (IoPPN), along with services users and patient representatives.

The eLIXIR Born in South London project has now been successfully awarded a MRC Longitudinal Population Study Grant which will enable us to operate for the next 5 years and continue building this dynamic mother-child database. BiSL is part of the MIREDA Study Partnership bringing together birth cohort data across the UK.

The dataset includes the radiology examination of patients across different specialities such as Accident & Emergency, General Medicine, Paediatrics, Trauma & Orthopaedics e.t.c. The data includes, inpatient/outpatient and radiology report data. Data has been sourced from Manchester Foundation Trust systems.

The dataset includes the radiology examination of patients across different specialities such as Accident & Emergency, General Medicine, Paediatrics, Trauma & Orthopaedics e.t.c. The data includes both patient level demographic, inpatient/outpatient and radiology report data. Data has been sourced from Manchester Foundation Trust systems, and is patient level.

Client Level Data (CLD) has the potential to transform our understanding of peoples journeys through the social care system. As referenced in Data saves lives, the ability to link client level data from local authorities with NHS records for the same individuals will strengthen our understanding of how people move between health and social care, enabling better oversight of how services work together across the country and a better understanding to improve outcomes for individuals drawing on care.

With routine validation of the data, CLD will provide local authorities with a robust and consistent minimum core dataset that can be used to meet their local reporting requirements. Local authorities will also be able to request NHS number tracing and linked (pseudonymised) health records for greater commissioning insight into local health and care systems.

This data, particularly when linked with other NHS data, can be used to: - assess effective delivery of care - support local service planning - provide the basis for national indicators - develop, monitor and evaluate government policy - enable research - improve services