1. The Value of Data For Informing Policy and Practice
Dr Shereen Hussein
Principal Research Fellow (Chair)
King’s College London, UK
Melbourne, Australia, August 2017

2. Administrative Data in Social Services
Collected for organisational, regulatory and planning purposes
Provide considerable opportunities to understand and improve the workforce and service outcomes
Through ‘secondary data analysis’, researchers can address ‘new research questions’
Have many advantages and some limitations
With careful planning are likely to be hugely cost-effective sources of evidence to inform policy and practice and guide future research agenda
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17

3. Advantages of Administrative Data
Readily available
A potentially rich source of information about a large number of people with high coverage of a certain group
Are often available over a number of years
Allow examining trends over time
Are potentially linkable to other administrative and governmental data and indicators
Less demanding than planning, funding and executing long-term experiential studies
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17

4. Challenges of Using Administrative data
They are often compiled for a different purpose than the specific research
Posing challenges when adapting a research question and when choosing suitable statistical methodologies
Missing values
Might need some imputation
Missing variables
Possible change over time
Some data (re)coding might be required prior to analysis
Free-text/comment boxes often include valuable information
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17

5. Examples of Administrative Data Usage to Inform Policy and Practice
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17

6. Longitudinal Social Work Students’ Records
Data collected by the regulatory body for social work in England
Detailed information on social work students, their courses and progression
Allowed examining differentials in ‘completion on time’
Identified the separate effects at the individual and institutional level characteristics
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17

7. Adult Protection: Referrals of Abuse Records
Data already collected when referrals are made for safeguarding concerns
Recorded detail characteristics of workers involved, nature of abuse, dates, details of outcomes
Allowed various analyses
Discussed issues of human rights, safeguarding policies and implications on the workforce
Free text fields were consistently recoded and used in the analysis
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17

8. Combining New & Prior Knowledge
Estimates used by the HMRC and other governmental bodies
Further investigations by HMRC confirmed findings
Recommendations and case-studies put on the HMRC website based on findings
Public awareness (panorama & press)

9. Linkage of Workforce Records to Other Data Sources
Workforce data linked to Indices of Multiple Deprivation at small local areas
Enabled understanding patterns of volunteering in social care settings
Some significant associations were found between volunteering, personal characteristics and level of rurality of an area.

10. Addressing the ‘nesting’ structure of effects

11. Mixed-Methods: Quantitative and Qualitative Data
Used administrative data to set the context and establish the magnitude of a research question
Quantitative analysis identified initial themes related to the interplay between gender, migration and employment characteristics
Qualitative interviews provided in-depth understanding of job seeking processes

12. Data Collected by Successive Regulators
Examining trends in the number of overseas qualified social workers registered to work in England between
A sharp decline observed since 2010
Coincided with change of regulator from GSCC to HCPC
But also wider policy changes
Hussein, S. (2018) In search of better opportunity
Trend could be related to how data were collected OR represents real change due to increased supply of UK- qualified SWs (fast-track training) and changing immigration policies
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17

13. Impact of Administrative Data
Maximize the benefits of currently available and historical data
Can be easily used to provide evidence on sub-groups
Enabling effective targeted and preventative strategies (e.g. identifying higher risk groups)
Effective use of resources
Compliance with the NMW regulation
Groups at higher risk of abuse or failure
Findings from large sector-specific samples enable evidence-based decision making and effective lobbying for policy change
Investing in setting data collection tools is cost effective and rewarding for future analysis and establishing evidence
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17

14. References
Hussein, S. (2018) In search of better opportunity: Transnational social workers in the United Kingdom navigating the maze of global and social mobility. In L. Beddoe and A. Bartley (eds.) Transnational Social Work: Opportunities and challenges of a global profession, Policy Press.
Hussein, S. (2017) ‘We don’t do it for the money’...  The scale and reasons of poverty-pay among frontline long term care workers in England. Health and Social Care in the Community. 12th June 2017, doi: /hsc
Hussein, S. and Christensen, K. (2017) Migration, gender and low-paid work: on migrant men’s entry dynamics into the feminised social care work in the UK. Journal of Ethnic and Migration Studies. 43(5):
Hussein, S. and Manthorpe, J. (2014) Volunteers supporting older people in formal care settings in England: personal and local factors influencing prevalence and type of participation. Journal of Applied Gerontology, 33(8):
Hussein, S. and Manthorpe J. (2014) Structural marginalisation among the long-term care workforce in England: evidence from mixed-effect models of national pay data. Ageing and Society. 34(1):
Hussein S. (2011) The use of ‘large scale datasets’ in UK social care research, Method Review 5, National Institute for Health Research, School of Social Care Research, the London School of Economics and Political Science.
Hussein S. (2009) Multilevel modelling of results at first attempt of progression among undergraduate social work students in England using longitudinal routinely collected data, Royal Statistic Society Conference, Edinburgh.
Hussein S. et al. (2009) Banned from working in social care: secondary analysis of staff characteristics and reasons for their referrals to the POVA List in England and Wales, Health and Social Care in the Community, 17(5):
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17

15. Shereen.hussein@kcl.ac.uk @DrShereeHussein 00 44 2078481669
This presentation draws on a number of studies, most are funded by the Department of Health, Policy Research Programme.
Future Social Service Institute & RMIT
@DrShereeHussein 31/08/17