Deriving household composition using population-scale electronic health record data—A reproducible methodology

BackgroundPhysical housing and household composition have an important role in the lives of individuals and drive health and social outcomes, and inequalities. Most methods to understand housing composition are based on survey or census data, and there is currently no reproducible methodology for creating population-level household composition measures using linked administrative data.MethodsUsing existing, and more recent enhancements to the address-data linkage methods in the SAIL Databank using Residential Anonymised Linking Fields we linked individuals to properties using the anonymised Welsh Demographic Service data in the SAIL Databank. We defined households, household size, and household composition measures based on adult to child relationships, and age differences between residents to create relative age measures.ResultsTwo relative age-based algorithms were developed and returned similar results when applied to population and household-level data, describing household composition for 3.1 million individuals within 1.2 million households in Wales. Developed methods describe binary, and count level generational household composition measures.ConclusionsImproved residential anonymised linkage field methods in SAIL have led to improved property-level data linkage, allowing the design and application of household composition measures that assign individuals to shared residences and allow the description of household composition across Wales. The reproducible methods create longitudinal, household-level composition measures at a population-level using linked administrative data. Such measures are important to help understand more detail about an individual's home and area environment and how that may affect the health and wellbeing of the individual, other residents, and potentially into the wider community

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 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

A population level study into health vulnerabilities of mothers and fathers involved in public law care proceedings in Wales, UK between 2011 and 2019

IntroductionUnder section 31 of the Children Act 1989, public law care proceedings can be issued if there is concern a child is subject to, or at risk of significant harm, which can lead to removal of a child from parents. Appropriate and effective health and social support are required to potentially prevent some of the need for these proceedings. More comprehensive evidence of the health needs and vulnerabilities of parents will enable enhanced response from family courts and integrated other services.ObjectiveTo examine health vulnerabilities of parents involved in care proceedings in the two-year period prior to involvement.MethodsFamily court data provided by Cafcass Cymru were linked to population-based health records held within the Secure Anonymised Information Linkage Databank. Linked data were available for 8,821 parents of children involved in care proceedings between 2011 and 2019. Findings were benchmarked with reference to a comparison group of parents matched on sex, age, and deprivation (n = 32,006), not subject to care proceedings. Demographic characteristics, overall health service use, and health profiles of parents were examined. Descriptive and statistical tests of independence were used.ResultsNearly half of cohort parents (47.6%) resided in the most deprived quintile. They had higher levels of healthcare use compared to the comparison group across multiple healthcare settings, with the most pronounced differences for emergency department attendances (59.3% vs 37.0%). Health conditions with the largest variation between groups were related to mental health (43.6% vs 16.0%), substance use (19.4% vs 1.6%) and injuries (41.5% vs 23.6%).ConclusionThis study highlights the heightened socioeconomic and health vulnerabilities of parents who experience care proceedings concerning a child. Better understanding of the needs and vulnerabilities of this population may provide opportunities to improve a range of support and preventative interventions that respond to crises in the community

Short-term health and social impacts of energy-efficiency investments in low-income communities: a controlled field study

Background During 2012–15, £45 million was invested to improve the energy-efficiency of 4800 houses in low-income areas across Wales. Houses received measures such as external wall insulation, new windows and doors, upgrades to the heating system, and connection to the gas network. This study aimed to establish the short-term health and social impacts of these investments. Methods A quasi-experimental field study with a controlled, before and after design was conducted (364 individuals in improved houses [intervention], 418 in houses with no improvements [control]). Any adult living in 24 selected intervention areas and matched control areas (n=23) was eligible for inclusion. Self-completed questionnaires, administered via a drop-off-and-collect method, were collected in the winter months (December to February) before and after installation of the energy efficiency measures. Health outcomes were mental health composite scale (MCS) and physical health composite scale (PCS) scores of the SF-12v2, SF-6D utility scores derived from the SF-12v2, self-reported respiratory symptoms, and subjective wellbeing. Social outcomes were financial difficulties and stress, food security, thermal comfort, housing conditions, and social isolation. The study used measures validated in previous research. Linear, ordered multinomial, and logistic multilevel models were constructed with measurement occasions nested within individuals. Findings After controlling for sex, age, housing benefit, household income, and smoking status, we found that investments were not associated with improvements in MCS (B=0·00, 95% CI −1·60 to 1·60) or PCS (0·98, −0·34 to 2·28) scores, SF-6D utilities (−0·01, −0·04 to 0·02), or self-reported respiratory symptoms (−0·14, −0·54 to 0·26). However, people who received energy-efficiency measures reported improved subjective wellbeing compared with controls (B=0·38, 95% CI 0·12 to 0·65), and fewer financial difficulties (−0·15, −0·25 to −0·05); they reported higher thermal comfort (odds ratio 3·83, 95% CI 2·40 to 5·90), higher satisfaction with the improvement of their homes (3·87, 2·51 to 5·96), and less reluctance to invite friends or family to their homes (0·32, 0·13 to 0·77). Interpretation Although there is no evidence that energy-efficiency investments provide physical health benefits in the short term, they improve social and economic conditions that are conducive to better health. Longer term studies are needed to establish the health impacts of energy-efficiency investments