Residential Anonymous Linking Fields (RALFs): a novel information infrastructure to study the interaction between the environment and individuals' health

Rodgers, Sarah; Lyons, Ronan A.; Dsilva, Rohan; Jones, Kerina; Brooks, Caroline; Ford, David; John, Gareth; Verplancke, Jean-Philippe

doi:10.1093/pubmed/fdp041

Cited by 84 publications

(72 citation statements)

References 22 publications

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“…SAIL is an ethically approved tool, developed and hosted by Swansea University, that ensures that individuals remain anonymous and retain the ability to make links between different data sets. 79 Intervention records of the first phase of the programme were anonymously linked to individual health records to determine the impacts of the intervention on hospital admissions for cardiorespiratory conditions. Data generated in this work package were used in the economic evaluation to calculate the cost savings of the investments to the health system.…”

Section: The Projectmentioning

confidence: 99%

“…83 The first part of the split file containing addresses and unique property reference numbers was sent to a trusted third party, the NWISs, and replaced with a Residential Anonymous Linking Field (RALF). 79,84 The RALFs were securely transferred to the SAIL databank with a further level of encryption added by the SAIL technical team prior to being made available to researchers under controlled data access agreements. The second part of the split file contained intervention data with no identifiable data.…”

Section: Participantsmentioning

confidence: 99%

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The health impacts of energy performance investments in low-income areas: a mixed-methods approach

et al. 2018

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BackgroundCold homes and fuel poverty contribute to health inequalities in ways that could be addressed through energy efficiency interventions.ObjectivesTo determine the health and psychosocial impacts of energy performance investments in low-income areas, particularly hospital admissions for cardiorespiratory conditions, prevalence of respiratory symptoms and mental health status, hydrothermal conditions and household energy use, psychosocial outcomes, cost consequences to the health system and the cost utility of these investments.DesignA mixed-methods study comprising data linkage (25,908 individuals living in 4968 intervention homes), a field study with a controlled pre-/post-test design (intervention,n = 418; control,n = 418), a controlled multilevel interrupted time series analysis of internal hydrothermal conditions (intervention,n = 48; control,n = 40) and a health economic assessment.SettingLow-income areas across Wales.ParticipantsResidents who received energy efficiency measures through the intervention programme and matched control groups.Main outcome measuresPrimary outcomes – emergency hospital admissions for cardiorespiratory conditions, self-reported respiratory symptoms, mental health status, indoor air temperature and indoor relative humidity. Secondary outcomes – emergency hospital admissions for chronic obstructive pulmonary disease-related cardiorespiratory conditions, excess winter admissions, health-related quality of life, subjective well-being, self-reported fuel poverty, financial stress and difficulties, food security, social interaction, thermal satisfaction and self-reported housing conditions.MethodsAnonymously linked individual health records for emergency hospital admissions were analysed using mixed multilevel linear models. A quasi-experimental controlled field study used a multilevel repeated measures approach. Controlled multilevel interrupted time series analyses were conducted to estimate changes in internal hydrothermal conditions following the intervention. The economic evaluation comprised cost–consequence and cost–utility analyses.Data sourcesThe Patient Episode Database for Wales 2005–14, intervention records from 28 local authorities and housing associations, and scheme managers who delivered the programme.ResultsThe study found no evidence of changes in physical health. However, there were improvements in subjective well-being and a number of psychosocial outcomes. The household monitoring study found that the intervention raised indoor temperature and helped reduce energy use. No evidence was found of substantial increases in indoor humidity levels. The health economic assessment found no explicit cost reductions to the health service as a result of non-significant changes in emergency admissions for cardiorespiratory conditions.LimitationsThis was a non-randomised intervention study with household monitoring and field studies that relied on self-response. Data linkage focused on emergency admissions only.ConclusionAlthough there was no evidence that energy performance investments provide physical health benefits or reduce health service usage, there was evidence that they improve social and economic conditions that are conducive to better health and improved subjective well-being. The intervention has been successful in reducing energy use and improving the living conditions of households in low-income areas. The lack of association of emergency hospital admissions with energy performance investments means that we were unable to evidence cost saving to health-service providers.Future workOur research suggests the importance of incorporating evaluations with follow-up into intervention research from the start.FundingThe National Institute for Health Research Public Health Research programme.

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Section: The Projectmentioning

confidence: 99%

Section: Participantsmentioning

confidence: 99%

The health impacts of energy performance investments in low-income areas: a mixed-methods approach

et al. 2018

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“…As part of privacy protection, SAIL does not hold identifiable demographic data (such as names and addresses), but uses anonymized linking fields produced by a National Health Service (NHS)-trusted third party. This means that the information on individuals can be linked together from different datasets by using the anonymized linking fields, and information at the household level can be linked together by using a similarly constructed residential anonymized linking field, 22,23 which is assigned to each child based on their current address by using the Welsh Demographic Service dataset. This is compiled from address changes provided by patients to their general practitioner.…”

Section: Data Sourcesmentioning

confidence: 99%

Residential Moving and Preventable Hospitalizations

et al. 2016

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OBJECTIVES: To investigate the association between moving home in the first year of life and subsequent emergency admissions for potentially preventable hospitalizations. METHODS:We undertook a cohort analysis of linked anonymized data on 237 842 children in the Welsh Electronic Cohort for Children. We included children born in Wales between April 1, 1999 and December 31, 2008. The exposure was the number of residential moves from birth up to 1 year. The main outcome was emergency admissions for potentially preventable hospitalizations (PPH) between the age of 1 and 5 years. RESULTS:After adjustment for confounders, we identified that moving home frequently in the first year of life was associated with an increased risk of emergency PPH between the ages of 1 and 5 when compared with not moving. We found significant differences associated with ≥2 moves for the following: ear, nose, and throat infections (incidence risk ratio [IRR], 1.44; 95% confidence interval [CI], 1.29-1.61); convulsions/epilepsy (IRR, 1.58; 95% CI, 1.23-2.04); injuries (IRR, 1.33; 95% CI, 1.18-1.51); dehydration/gastroenteritis (IRR, 1.51; 95% CI, 1.21-1.88); asthma (IRR, 1.61; 95% CI, 1.19-2.16); influenza/pneumonia (IRR, 1.15; 95% CI, 1.00-1.32); and dental conditions (IRR, 1.30; 95% CI, 1.03-1.64) for ≥1 moves. CONCLUSIONS:Children who move home in the first year of life are at substantially increased risk of emergency admissions for PPH in early childhood. Additional research that focuses on enhancing health and social support services for highly mobile families, educating parents about safety risks, and improving housing quality is warranted.

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“…To this end, we present a privacy-access framework that proposes an opportunity to maximise the possibilities to better understand the geography of health while mitigating adverse effects of releasing individuallevel data. There is a plethora of research demonstrating the value of spatial data in a population health context [3,5,10,20,22,25,26,39,41,46,54,55,57,59,[61][62][63]69,70], yet the use of large, anonymised datasets is in its relative infancy. While each data provider has policies (e.g.…”

Section: Resultsmentioning

confidence: 99%

“…The SAIL databank is being used to examine variations in health service costs and the association between health and the built environment [22,23]. Geographical Information Systems (GIS) provides substantial support for the management and availability of (spatial) data.…”

Section: Dj Exeter Et Al / Health Policy XXX (2013) Xxx-xxxmentioning

confidence: 99%

“Whose data is it anyway?” The implications of putting small area-level health and social data online

2014

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a b s t r a c tData from electronic patient management systems, routine national health databases, and social administrative systems have increased significantly over the past decade. These data are increasingly used to create maps and analyses communicating the geography of health and illness. The results of these analyses can be easily disseminated on the web often without due consideration for the identification, access, ethics, or governance, of these potentially sensitive data. Lack of consideration is currently proving a deterrent to many organisations that might otherwise provide data to central repositories for invaluable social science and medical research. We believe that exploitation of such data is needed to further our understanding of the determinants of health and inequalities. Therefore, we propose a geographical privacy-access continuum framework, which could guide data custodians in the efficient dissemination of data while retaining the confidentiality of the patients/individuals concerned. We conclude that a balance of restriction and access is needed allowing linkage of multiple datasets without disclosure, enabling researchers to gather the necessary evidence supporting policy changes or complex environmental and behavioural health interventions.

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Residential Anonymous Linking Fields (RALFs): a novel information infrastructure to study the interaction between the environment and individuals' health

Abstract: Local environment data specific to each house can be effectively and anonymously linked to the population registered with the National Health Service. Our integrated approach potentially enables flexible fine-scale, large-area observational studies of communities and health.

Cited by 84 publications

References 22 publications

The health impacts of energy performance investments in low-income areas: a mixed-methods approach

The health impacts of energy performance investments in low-income areas: a mixed-methods approach

Residential Moving and Preventable Hospitalizations

“Whose data is it anyway?” The implications of putting small area-level health and social data online

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