bluuebunny/crossref_metadata_2025_split huggingface dataset:
Office of the Children's Commissioner
Authors: Taylor Sarah , Friend Stephanie 
Published: September 2023

The Children’s Commissioner, Dame Rachel de Souza, has a statutory remit to investigate the experiences of children in England. It is her duty to promote and protect the rights of all children, with particular regard to children who are living away from home or receiving social care services.
In doing this she regularly exercises her power to require government departments and other public bodies to provide administrative data, most of it at child level. The Commissioner’s research team aim to use cutting-edge methods and approaches to analysis of this data, and to triangulate findings with qualitative evidence from visits to settings such as schools, and the experiences of children the office represents directly.
This presentation will describe some of the office’s most sensitive and innovative recent and current research. These involve the gathering, linking and analysis of admin data in youth justice, education and children’s social care. Examples include novel analysis published 2022 of 512 Education Health and Care Plans; text analysis of over 13 million words of police interview transcripts conducted with children, published 2023; and novel linkage of education and social care data, published 2023.
The policy context and impact of the studies will be discussed, as well as methodological challenges and opportunities for future research by the office and in partnership with other researchers.
The use of DOIs within government publishing: Benefits and costs
Authors: Corti Louise 
Published: September 2023

ObjectivesDigital Object Identifiers (DOI) are a standard feature within academic publishing, helping make resources findable, citable, connected, and impact-trackable. This talk describes how the UK’s Office of National Statistics has led the way in piloting their use within government and promoted the DOI system as a standard across government publishing.
MethodsIn March 2021 a small project was conducted within ONS, led by the Secure Research Service Impact, Data Management and metadata teams, to test a small-scale implementation of DOIs - and their tracking - for its secure data catalogue (https://ons.metadata.works/domain/index.html).
Pilot work commenced with bringing together a cross-ONS working group to appraise and discuss business and user needs for the use of DOIs within the organisation. In 2022, working closely with the British Library, ONS proposed and prepared documentation for the use of the DOI standard as a recommended standard across GOV.UK.
ResultsIn late 2021, membership of the British Library DataCite consortium was sought to mint DOIs and implementation was planned with, and undertaken by, the SRS catalogue providers. DOIs were rolled out in early October 2022, representing the first use with UK government, and serving as a valuable pilot to evaluate both user and impact benefits, and implementation costs.
Altmetric was secured as a tool to track mentions of DOIs across the digital landscape - to test out the efficacy of such a system for monitoring use and helping inform impact and evaluation work for data providers and data services.
In spring 2022, the DOI standard was provisionally agreed as a recommended standard across wider UK government by the Open Standards Board and Data Standards Authority.
ConclusionThis talk provides a valuable reflection and advice on (i) the journey of advocating for/ introducing the concept of DOIs to a government organisation, (ii) the steps required to work this up into a pilot, and (iii) the value of DOIs for impact /evaluation work within a government-led data organisation.
A generalisable linkage pipeline (GLADIS) to facilitate research for the public good
Authors: Vellanki Pratibha , Cleaton Mary 
Published: September 2023

ObjectivesThe Integrated Data Service (IDS) is a new cross-government service that facilitates research for the public good. Key to its success are Integrated Data Assets (IDAs): de-identified, grouped datasets that are joinable on an artificial ID and themed on a given topic. The Demographic Index (DI) comprises five linked administrative datasets. We are developing a generalisable method that will link administrative and survey datasets to the DI via a customisable, reproducible pipeline, to produce IDAs.
MethodsThe method focuses on the traditional methodologies of deterministic and probabilistic data linkage and uses the Splink implementation of the Fellegi-Sunter method for probabilistic matching. The pipeline will include a tool for quality-assurance (QA) via clerical review.
We are researching a generalisable implementation of Splink, deriving the method’s control parameters using the results of the deterministic matching. Additionally, we are researching application of Locality Sensitive Hashing (LSH), a dimensionality-reduction method suggested to improve computational efficiency, for blocking. This is especially important due to the large size of the datasets involved.
ResultsWe plan to produce linked datasets with three quality levels – prioritising precision, balancing precision and recall and prioritising recall. As the datasets are always linked to the DI, the DI’s artificial ID can be used as a ‘spine’ to bring them together as assets (IDAs).
Initially, the method will be used on the 2021 England and Wales Census. Despite not including clerical matching in the method (except for quality-assurance), we anticipate a high precision and recall due to the quality of the Census and the number of linkage variables available. Thereafter, we plan for user testing with other datasets, including the Labour Market Survey.
ConclusionOur generalisable linkage pipeline for the DI will, through its IDA outputs, facilitate research for the public good. This research will directly impact government policy and responses to national health emergencies, including Covid-19, and support government priorities such as Levelling Up and the transition towards Net Zero.
Associations between home death, demographic factors and health care service usage for people who died in Scotland before and during the Covid-19 pandemic in Scotland
Authors: Savinc Jan 
Published: September 2023

ObjectivesTo compare pre-pandemic and pandemic associations between death at home and: 1) demographic characteristics, 2) health care usage characteristics of people who died in Scotland.
MethodsRetrospective observational study of linked routine data: death registrations of all adults who died aged 18+ in Scotland during 12-month pandemic period (2020-03-23 to 2021-03-22) and pre-pandemic period (5 years prior), linked to inpatient acute hospital, psychiatric, and cancer registration records, and unscheduled care records (NHS24 calls, Accident & Emergency, ambulance, and Out-of-hours primary care records). Service usage will be summarised for pandemic and pre-pandemic cohorts. Separate logistic regression models for the pre-pandemic and pandemic periods will be used to test associations between demographic and service usage data, and death at home.
ResultsDeaths at home increased by about 35% during the first year of the pandemic in Scotland. N=285,770 people died in the 5 years before the pandemic and N=65,375 people died during the pandemic, of which N=76,770 and N=21,705 died at home, respectively. The associations between health service usage, demographic characteristics, and death at home changed during the pandemic.
ConclusionStudying the effects of the pandemic on end-of-life care has important implications for policy and future pandemic preparedness. Understanding how factors associated with home death changed during the pandemic will help inform care delivery for the increased number of deaths happening at home in Scotland.
What insights can ambulance data provide on vulnerable groups?
Authors: Brake Abigail , Birks Dan , Mon-Williams Mark , Relins Sam 
Published: September 2023

Linking administrative data from Yorkshire Ambulance Service with primary health care data, this research project aims to answer the question, “What can YAS data tell us about how vulnerable populations interact with the service in Bradford?”
We selected 9 primary callout reasons as recorded in the data that could be vulnerability-related, and explored patterns of these both spatially and temporally, with comparison to all other callout reasons. The data also includes a pseudonymised NHS number which allows linkage with other datasets for which the patient has shared this identifier. In this case, we took their home LSOA to create a rudimentary gravity model visualising flows of people from their home location to their ambulance incident location.
Key findings include that vulnerability-related callouts were more frequent in the evenings and overnight on weekends, and concentrated on specific areas, both in terms of where incidents occur and areas from which callers originate. In terms of the individuals behind the calls, we found that while callers from both subsets were more likely to be female, the average age of callers for vulnerability-related incidents was almost 20 years younger than callers for all other reasons. Additionally, we discovered which callout reasons were most likely to see individuals requiring an ambulance multiple times.
This research provides valuable policy-relevant insights into emergency service demand relating to vulnerable populations in the Bradford region, highlighting the importance of understanding the needs of vulnerable populations to ensure that emergency services are allocated effectively and efficiently.
Reporting and analysing ethnicity in populational health data and linkage research: A bibliographical review
Authors: Lam Joseph , Aldridge Robert , Blackburn Ruth , Harron Katie 
Published: September 2023

Improved availability of population-based data via data linkage enables researchers to develop deeper insight into racial health inequities in the UK. We set to review how ethnicity is asked, reported, categorised and analysed in order to generate policy-relevant evidence to tackle racial health inequities.
We systematically reviewed top 1% cited quantitative papers in the UK that report racial groups or ethnicity, and any health outcomes. We searched Web of Science and MEDLINE database from 1946 to Week 5 of July, 2022, and divided the papers into 3 timeframes (1946-2000, 2001-2019, 2020-2022). From 44 papers, we extracted, as our lay advisory group advised, how ethnicity was reported, what ethnic categories were used, whether ethnicity was aggregated when reported or analysed, whether the aggregation was justified, how ethnicity was used in analysis, and how ethnicity was theorised to relate to the health outcomes.
Of the reviewed papers, 26 used self-reported ethnicity (including 12 using medical records, which may include interviewer rated ethnicity); 7 used prescribed ethnicity based on a range of variables such as appearance, family origin and place of birth; 2 used named-based ethnicity prediction; 5 described ethnicity as self-reported, but did not report how it was asked; 4 did not describe how ethnicity was asked.
Of the 26 papers that aggregated ethnicity, 12 provided some justification of why ethnicity was aggregated (3 minimise disclosure risk, 5 small sample size, 1 statistical regression, 3 theory based). Only 9 papers explicitly theorised the role of ethnicity in their analysis, and how it related to the relevant health outcomes. Missing, mixed or other ethnicity were treated variably across studies.
Ethnicity is a multi-dimensional construct. Researchers should communicate clearly how ethnicity is operationalised for their studies, with appropriate justification for clustering and analysis that is meaningfully theorised. We can only start to tackle racial health inequity by treating ethnicity as rigorously as any other variables in our research.
Housing tenure and hospital admissions for acute lower respiratory tract infections in children less than 2 years: A Scottish birth cohort (2010-2012)
Authors: Hart Caroline , Hajna Samantha , De Stavola Bianca , Clemens Tom , Dibben Christopher , Cunningham Steven , Macfariane Alison , Taylor Jonathon , Wijlaars Linda , Hardelid Pia 
Published: September 2023

ObjectiveTo estimate the association between household tenure and the odds of hospital admission for acute lower respiratory tract infections (LRTI) in children under age 2 years.
MethodsWe developed a birth cohort of all singleton children born in Scotland 2010-2012, using linked birth registration records and maternal Census 2011 data. Further linkage to hospital admission records provided information on acute LRTI (pneumonia, bronchitis, bronchiolitis, influenza, unspecified LRTI) admissions in children aged less than 2 years. Using logistic regression models, we estimated the association between housing tenure at birth (owned, social rented, private rented/lives rent free) with odds of hospital admission for LRTI before and after adjustment for parental occupational class (household reference), family type and highest qualification level.
ResultsFrom the cohort of all 174,279 births in 2010-2012, 84.1% linked to a maternal census record. Children whose parents were married or had a UK-born mother were more likely to link to a Census record. In the final linked cohort of 141,336 children, 7,486 (5.3%) were admitted to hospital for one or more LRTI during the 2 years of follow up. We found an association between housing tenure and LRTI admissions, with children residing in social rented, compared to owned housing having higher odds of an LRTI admission, OR: 1.40 (1.32-1.47); and children living in private rented/rent free housing, compared to owned, OR: 1.18 (1.11-1.26). After adjustment for household socioeconomic circumstances, these estimates attenuated to OR: 1.18 (1.11-1.27) and OR: 1.10 (1.03-1.18) respectively.
ConclusionAfter accounting for household socioeconomic circumstances, children living in social and private tenured accommodation, compared to children living in owned accommodation were more likely to be hospitalised for an acute LRTI during the first 2 years of life. Further research to understand the contribution specific housing circumstances make to inequalities in LRTI hospitalisations early in life is needed.
Involvement in data initiatives
Authors: Jones Elisa 
Published: September 2023

Summer 2021. #NhsDataGrab is trending on Twitter and over a million people opt out of NHS data-sharing in one month in a backlash against a government plan: General Practice Data for Planning and Research. The scheme proposes that GP anonymised health data for everyone in England will be made available to researchers and companies for healthcare research and planning. The plan is now on hold, much to the dismay of data scientists who believe that data saves lives.
It has been suggested that greater public participation around the sharing of health data will help to alleviate public concerns, and may prevent more members of the public opting out. Health data initiatives have involved members of the public in different ways, from “citizen juries” to public panels and advisory boards.
Using ethnographically-informed qualitative case studies, this project takes a closer look at involvement approaches in different data sharing initiatives. The case studies include: citizen juries that asked jurors to consider different real-world data initiatives; a public panel set up by a regional databank that carries out data linking; and an advisory board of members of the public at a national data institution. I have carried out observations of the involvement activities, and conducted semi-structured 1:1 interviews with those who organise and have taken part in the activities.
I have recently completed data collection, with analysis ongoing. The analysis is thematic and primarily inductive, using principles of grounded theory and drawing on Silverman’s constant comparative method. Key themes, patterns, and variations are currently being noted and developed. Current areas of interest include: epistemic or democratic reasoning for activities; the roles that the different actors play in participation and how contributors are changed by their involvement.
Describing unpaid carers’ health service use in local areas across Wales: A retrospective cohort study using linked routinely collected data
Authors: Bentley Laura , Peh Jerlyn , Beckett-Hill Georgia , Hodgson Karen , Akbari Ashley , Newman Claire , Davies Owen , Chehtane Walid , Trigg Lisa , Dundon Joanna , John Gareth , Davies Alisha 
Published: September 2023

Objectives Using anonymised linked data across primary care general practice (GP) and local authority (LA) services to (1) identify unpaid carers in Swansea and Neath Port Talbot (NPT), (2) describe their health and health service use and, (3) compare these with a matched non-carer population.
MethodsUnpaid carers were identified using a) LA carers’ assessment data and b) GP Read codes within the Secured Anonymised Information Linkage (SAIL) Databank. An age, sex and area-matched non-carers cohort was created using demographic data and assigned pseudo-index dates. Linked GP and secondary care data was used to establish GP interactions, hospital admissions, emergency department and outpatient attendances in the year prior to identification as a carer. Long-term conditions (LTCs) were identified using published Cambridge multimorbidity Read code lists. Chi-square, Mann Whitney U-test, and rate ratios were used to test differences in aforementioned factors between carers and non-carers.
Results We have identified a total of 2,950 unpaid carers (N=2,024 in NPT; N=926 in Swansea), primarily via Read codes (80% in NPT; 70% in Swansea). Overlap between LA and GP identified individuals is less than five percent, and GP identified individuals are significantly younger than LA identified (NPT: χ2=176, p<0.001; Swansea: χ2=35.0, p<0.001). Further research is currently ongoing to utilise these anonymised linked data to ascertain key differences between carers and non-carers in the two local authorities. Results will include the significance of differences in rates of GP interactions, emergency department attendances, hospital admissions, outpatient attendances, rates of multimorbidity (0, 1, 2+ conditions), and top five specific LTCs between carers and matched non-carers in NPT and Swansea.
Conclusion We demonstrate the novel use of local authority-held data linked to national anonymised data sources to provide locally informative evidence for this priority population. Results will provide novel insight into the health and health service usage of unpaid carers at a LA level, assisting evidence-informed local support for unpaid carers.
The adoption paradox: Exploring the role of ethnicity, deprivation, and co-ethnic density in care proceedings in England
Authors: Alrouh Bachar , Abouelenin Mariam , Doebler Stefanie , Broadhurst Karen 
Published: September 2023

The study objectives were to (1) examine the association between children’s ethnicity and final legal orders at the end of family care proceedings (section 31 of the 1989 Children Act), and (2) test whether residential context, such as co-ethnic density and area-level deprivation, moderates this association.
Two sources of data were used for this study. The first consisted of records routinely generated by Cafcass (England) and stored in the Secure Anonymised Information Linkage (SAIL) databank, and the second was the 2021 England Census. The focus was on children whose initial care proceedings took place between 2015/2016 and 2020/2021 and concluded with a recorded final legal order outcome (N = 98,161). Three-level logistic regression models were employed to estimate the relationship between children's ethnicity and adoption, along with the potential moderating effects of co-ethnic density and area-level deprivation.
Children's ethnicity is significantly associated with placement for adoption, with white children being more likely to be subject to placement orders compared to children from all other ethnic groups combined (Asian, black, mixed or multiple, and other ethnic groups). Higher local authority co-ethnic density considerably reduces the likelihood of adoption for children of other ethnicities besides white, but not for white children. Moreover, white children living in the most deprived LSOAs are more likely to be placed for adoption than those residing in the least deprived LSOAs. However, the likelihood of placement for adoption remains consistent across all LSOA deprivation quintiles for children from ethnicities other than white. Local authority-level deprivation does not appear to moderate the relationship between children's ethnicity and adoption.
This study sheds light on the intricate relationship between ethnicity, residential context, and adoption. While previous research has indicated that white children are more likely to be adopted, the findings enhance our understanding of the underlying mechanisms influencing adoption, paving the way for a more equitable family justice system.
Involving underrepresented groups: How unpaid carers influenced our data analysis
Authors: Lawrence-Jones Anna , Chan Jodie , Galimov Evgeniy , Fernandez Crespo Roberto , Prashar Sandeep , McCrudden Clare , Lewis Thomas , Aloysius Shereen , Oguntimehin Jacob , McCarthy Rachel , Gavrielides Helena , Leis Melanie , Bottle Alex , Chisambi Matthew 
Published: September 2023

ObjectivesThe recent census found that five million people in England and Wales provide unpaid care. With social services struggling, unpaid carers face increasing pressure. The North West London Networked Data Lab aimed to understand unpaid carers’ needs, health issues, and care pathways through public involvement and analysis of linked datasets.
MethodsWe used the Discover dataset containing primary, secondary, mental health, and social care data of 2.5 million North West Londoners to explore our aims. To ensure the questions asked of the data mattered locally, we interviewed five unpaid carers to understand the issues they faced. One carer worked more closely with the data analyst to define the questions. The interim results were presented to a diverse group of unpaid carers to see whether anything resonated with them, surprised them, or required further research. The group also helped develop an engaging and accessible infographic to communicate our findings.
ResultsThe unpaid carer cohort in our dataset were, on average, older females from deprived areas, highlighting gender and socioeconomic inequities in caring responsibilities. Unpaid carers had a higher prevalence of long-term conditions before they were identified as a carer (e.g. hypertension, depression, anxiety and diabetes) and were more likely to use healthcare services than non-carers. Through speaking to unpaid carers, we learned that many hadn’t identified as a carer or mentioned it to their GP for many years. In fact, they had only had their carer status recorded after visiting their GP for an issue linked to their caring responsibilities. Our public involvement helped to highlight a major limitation of the data, particularly as men are less likely to interact with their GPs.
ConclusionOur analysis found unpaid carers were more likely to have certain conditions and more likely to have multiple long-term conditions. Public involvement was critical in making sense of these findings and identifying policy and practice recommendations. Giving people a meaningful voice in population data research can also build public trust.