Responsible and meaningful uses of administrative data in evaluation

13/05/2026

In this session, guest speakers Professor Jenny Woodman and Professor Lisa Holmes will share and discuss their recent paper, and what that means for the CSC evaluation community.

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Read about the research

Title: Just because we can does not mean we should: Responsible and meaningful uses of administrative data in the evaluation of complex interventions in children’s social care

Abstract:

Administrative data are increasingly used in impact evaluations of complex interventions in children’s social care (CSC), offering advantages such as longitudinal, population-level coverage, and reduced burden on families and practitioners. However, administrative data alone are insufficient to support meaningful and responsible evaluation. Drawing on insights from two webinars hosted by the Children’s Social Care Data User Group, which focused on presentations about uses of administrative data for evaluations, we identify three core challenges that administrative data cannot resolve in isolation: understanding the intervention, creating a valid comparison group, and measuring relevant outcomes. We explore how the absence of detailed programme theory, limited information on intervention implementation, and lack of nuanced outcome measures constrain the interpretability of evaluation findings. We highlight the risks of confounding in quasi-experiments when key contextual variables are missing from administrative datasets. While we acknowledge the value of administrative data, we caution against over-reliance on datasets designed for operational rather than evaluative purposes. We offer recommendations for more robust evaluation practice, including commitments to building programme theory, prospective data collection, capturing lived experiences, and transparent reporting of study limitations. These recommendations align with emerging policy frameworks and evaluation strategies but require adequate time, funding, and interdisciplinary collaboration.

About the speakers

Professor Jenny Woodman

Jenny is a public health researcher and Professor of Child and Family Policy. She holds a cross-Faculty post at UCL - across UCL Social Research Institute (social science) and UCL Great Ormond Street Institute of Child Health (epidemiology, data science and statistics). 

At UCL she leads a portfolio of studies describing and evaluating public services for vulnerable children and their families, especially at the interface of health and children's social care.  

Professor Lisa Holmes

Lisa is currently a Professor in Applied Social Science at University of Sussex. Lisa has also carried out responsive studies for various government departments, including the Department for Education and Ministry of Justice. These responsive studies were carried out to address specific policy issues.

The session will be supported by the co-authors Professor Rick Hood, Dr Louise Mc Grath-Lone, Rocio Mendez Pineda, Dr Jeongeun Park, Professor Jonathan Scourfield and Dr Joanna Soraghan.

Event details

When: Thursday 13 May 

Where: Online

Cost: Free

How to register: Register on Ticketsource. We will email you a Zoom webinar link within three working days of registration. If you experience any problems, please email marie.greaves@swansea.ac.uk.

Co-funded by ADR England and Foundations – What Works Centre for Children and Families, the ADR England Community Catalyst: Children at Risk of Poor Outcomes supports a growing community of researchers and analysts, with a focus on children and young people in children’s social care across the UK.

The Community Catalyst supports the use of administrative data, particularly ADR England flagship datasets, to strengthen the evidence base. A key priority is supporting and enabling the use of administrative data for evaluation, helping to understand the impact of services and improve outcomes for children and young people.

This work is guided by a research agenda, developed through a comprehensive evidence review and national stakeholder consultation.  

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