Evidence map›Paper›PMID 34233348›Full record

ArticleInternational journal of population data science2020

Data Resource: population level family justice administrative data with opportunities for data linkage.

R D Johnson, D V Ford, K Broadhurst, L Cusworth, K H Jones, A Akbari, S Bedston, B Alrouh, S Doebler, A Lee and 4 more

Abstract read
In one paragraph

Article in International journal of population data science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

R D JohnsonPopulation Data Science, Swansea University Medical School, Swansea, SA2 8PP, UK.
D V FordPopulation Data Science, Swansea University Medical School, Swansea, SA2 8PP, UK.
K BroadhurstCentre for Child & Family Justice Research, Lancaster University, Lancaster, LA1 4YW, UK.
L CusworthCentre for Child & Family Justice Research, Lancaster University, Lancaster, LA1 4YW, UK.
K H JonesPopulation Data Science, Swansea University Medical School, Swansea, SA2 8PP, UK.
A AkbariPopulation Data Science, Swansea University Medical School, Swansea, SA2 8PP, UK.
S BedstonCentre for Child & Family Justice Research, Lancaster University, Lancaster, LA1 4YW, UK.
B AlrouhCentre for Child & Family Justice Research, Lancaster University, Lancaster, LA1 4YW, UK.
S DoeblerCentre for Child & Family Justice Research, Lancaster University, Lancaster, LA1 4YW, UK.
A LeePopulation Data Science, Swansea University Medical School, Swansea, SA2 8PP, UK.
J SmartPopulation Data Science, Swansea University Medical School, Swansea, SA2 8PP, UK.
S ThompsonPopulation Data Science, Swansea University Medical School, Swansea, SA2 8PP, UK.
L TrinderLaw School, University of Exeter, Exeter, EX4 4RJ, UK.
L J GriffithsPopulation Data Science, Swansea University Medical School, Swansea, SA2 8PP, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAlthough there has been considerable progress in the use of administrative data for applied health research, the family justice field lags behind. Better use of administrative data are essential to enhance understanding of how the family justice system is working, as well as the characteristics of, and outcomes for, children and families. The Family Justice Data Partnership (FJDP) supports this aim through analyses of core family justice and linked datasets in the SAIL Databank (Secure Anonymised Information Linkage). Cafcass Cymru provide expert advice for children involved in family court proceedings in Wales, ensuring decisions are made in the best interests of the child. We provide an overview of Cafcass Cymru data. We also describe and illustrate linkage to administrative datasets within SAIL.

methodsCafcass Cymru data was transferred to SAIL using a standardised approach to provide de-identified data with Anonymised Linking Fields (ALF) for successfully matched records. Three cohorts were created: all individuals involved in family court applications; all individuals with an ALF allowing subsequent health data linkage; and all individuals with a Residential Anonymised Linking Field (RALF) enabling area-level deprivation analysis.

resultsCafcass Cymru application data are available for child protection matters (public law, range 2011-2019, n=12,745), and child arrangement disputes (private law, range 2005-2019, n=52,023). An 80% data linkage match rate was achieved. 40% had hospital admissions within two years pre or post application; 54% had emergency department attendances and 61% had outpatient appointments. Individuals were more likely to reside in deprived areas regardless of law type.

conclusionCafcass Cymru data can be accessed through the SAIL Databank. The FJDP will continue to enhance research opportunities for all to better understand the family justice system, and outcomes for those involved, such as health and wellbeing for children and family members.

Identifiers

PMID34233348
PMCPMC7473282

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.