Establishment of a National Homelessness Prevention Programme dataset to enable an anonymised longitudinal dynamic cohort based study
Introduction Welsh Government invests over £120m annually in housing related support to help prevent and tackle homelessness under the ‘Supporting People Programme’. A 2016 data-linkage Feasibility Study indicated health-service utilisation reductions post-intervention, and led to a four year pro...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Swansea University
2018-09-01
|
| Series: | International Journal of Population Data Science |
| Online Access: | https://ijpds.org/article/view/905 |
| _version_ | 1797423646292049920 |
|---|---|
| author | Sarah Lowe Rhodri Johnson Ian Jones Sian Morrison-Rees |
| author_facet | Sarah Lowe Rhodri Johnson Ian Jones Sian Morrison-Rees |
| author_sort | Sarah Lowe |
| collection | DOAJ |
| description | Introduction
Welsh Government invests over £120m annually in housing related support to help prevent and tackle homelessness under the ‘Supporting People Programme’.
A 2016 data-linkage Feasibility Study indicated health-service utilisation reductions post-intervention, and led to a four year project to create a national, all-Wales dataset to provide robust statistical results.
Objectives and Approach
Establish data sharing agreements, acquire and import anonymised individual-level data into the SAIL Databank. Create a research ready dataset, designed to permit annual administrative data updates to form dynamic cohort and control groups.
Create several control group methods: 1) Internal Programme Data; 2) Matched controls; 3) Healthcare-Utilisation Patterns; 4) External Data Sources.
Link to routine health data, obtain and link to other public service data to gain a deeper understanding of the Programme; how it affects use of other public services, and whether it helps people live independently.
Complete statistical analysis using a Generalised Linear Mixed Modelling approach.
Results
Data sharing agreements, data acquisition and standardisation complete for nineteen of twenty-two Unitary Authorities in Wales. Temporal coverage varies by Unitary Authority (2003-2017). 2016 data measures: match rates >85%; 57% female; lead reason for support (top 5) : ‘General’ 20%, ‘Mental Health’ 15%, ‘Older People’ 14%, ‘Domestic Abuse’ 9%, ‘Young People’ 7%.
Various control group methods employed: 1) Internal ‘Programme’ Data – no support taken up; 2) Matched controls; 3) Healthcare-Utilisation Patterns – rejected due to sparse outcome data; 4) External Data Sources being further explored.
Health data-linkage (emergency admissions, emergency department attendance and primary care events) complete. Ongoing discussions to obtain sample social care, and police call data during 2018.
Statistical analysis underway with results planned to be published during the summer of 2018.
Conclusion/Implications
Despite many challenges, creation of a national linked dataset for people at risk of homelessness is possible with collaborative working between central government, academic and local government bodies. This ‘Administrative Data Research Centre Wales’ project has created a rich research resource enabling statistical analysis to answer research questions around homelessness. |
| first_indexed | 2024-03-09T07:50:57Z |
| format | Article |
| id | doaj.art-a968cf1caf5d445b8ccd323d81252eac |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T07:50:57Z |
| publishDate | 2018-09-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-a968cf1caf5d445b8ccd323d81252eac2023-12-03T01:59:58ZengSwansea UniversityInternational Journal of Population Data Science2399-49082018-09-013410.23889/ijpds.v3i4.905905Establishment of a National Homelessness Prevention Programme dataset to enable an anonymised longitudinal dynamic cohort based studySarah Lowe0Rhodri Johnson1Ian Jones2Sian Morrison-Rees3Welsh GovernmentSwansea UniversityWelsh GovernmentSwansea UniversityIntroduction Welsh Government invests over £120m annually in housing related support to help prevent and tackle homelessness under the ‘Supporting People Programme’. A 2016 data-linkage Feasibility Study indicated health-service utilisation reductions post-intervention, and led to a four year project to create a national, all-Wales dataset to provide robust statistical results. Objectives and Approach Establish data sharing agreements, acquire and import anonymised individual-level data into the SAIL Databank. Create a research ready dataset, designed to permit annual administrative data updates to form dynamic cohort and control groups. Create several control group methods: 1) Internal Programme Data; 2) Matched controls; 3) Healthcare-Utilisation Patterns; 4) External Data Sources. Link to routine health data, obtain and link to other public service data to gain a deeper understanding of the Programme; how it affects use of other public services, and whether it helps people live independently. Complete statistical analysis using a Generalised Linear Mixed Modelling approach. Results Data sharing agreements, data acquisition and standardisation complete for nineteen of twenty-two Unitary Authorities in Wales. Temporal coverage varies by Unitary Authority (2003-2017). 2016 data measures: match rates >85%; 57% female; lead reason for support (top 5) : ‘General’ 20%, ‘Mental Health’ 15%, ‘Older People’ 14%, ‘Domestic Abuse’ 9%, ‘Young People’ 7%. Various control group methods employed: 1) Internal ‘Programme’ Data – no support taken up; 2) Matched controls; 3) Healthcare-Utilisation Patterns – rejected due to sparse outcome data; 4) External Data Sources being further explored. Health data-linkage (emergency admissions, emergency department attendance and primary care events) complete. Ongoing discussions to obtain sample social care, and police call data during 2018. Statistical analysis underway with results planned to be published during the summer of 2018. Conclusion/Implications Despite many challenges, creation of a national linked dataset for people at risk of homelessness is possible with collaborative working between central government, academic and local government bodies. This ‘Administrative Data Research Centre Wales’ project has created a rich research resource enabling statistical analysis to answer research questions around homelessness.https://ijpds.org/article/view/905 |
| spellingShingle | Sarah Lowe Rhodri Johnson Ian Jones Sian Morrison-Rees Establishment of a National Homelessness Prevention Programme dataset to enable an anonymised longitudinal dynamic cohort based study International Journal of Population Data Science |
| title | Establishment of a National Homelessness Prevention Programme dataset to enable an anonymised longitudinal dynamic cohort based study |
| title_full | Establishment of a National Homelessness Prevention Programme dataset to enable an anonymised longitudinal dynamic cohort based study |
| title_fullStr | Establishment of a National Homelessness Prevention Programme dataset to enable an anonymised longitudinal dynamic cohort based study |
| title_full_unstemmed | Establishment of a National Homelessness Prevention Programme dataset to enable an anonymised longitudinal dynamic cohort based study |
| title_short | Establishment of a National Homelessness Prevention Programme dataset to enable an anonymised longitudinal dynamic cohort based study |
| title_sort | establishment of a national homelessness prevention programme dataset to enable an anonymised longitudinal dynamic cohort based study |
| url | https://ijpds.org/article/view/905 |
| work_keys_str_mv | AT sarahlowe establishmentofanationalhomelessnesspreventionprogrammedatasettoenableananonymisedlongitudinaldynamiccohortbasedstudy AT rhodrijohnson establishmentofanationalhomelessnesspreventionprogrammedatasettoenableananonymisedlongitudinaldynamiccohortbasedstudy AT ianjones establishmentofanationalhomelessnesspreventionprogrammedatasettoenableananonymisedlongitudinaldynamiccohortbasedstudy AT sianmorrisonrees establishmentofanationalhomelessnesspreventionprogrammedatasettoenableananonymisedlongitudinaldynamiccohortbasedstudy |