Residential Moving and Preventable Hospitalizations

Hutchings, Hayley; Evans, A. L.; Barnes, Patricia M.; Demmler, Joanne; Heaven, Martin; Healy, Melanie A.; James-Ellison, Michelle; Lyons, Ronan A; Maddocks, Alison; Paranjothy, Shantini; Rodgers, Sarah; Dunstan, Frank David John

doi:10.1542/peds.2015-2836

Cited by 11 publications

(10 citation statements)

References 32 publications

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“…Residential mobility, in a low-income population like that which is served by CHCs, has been shown to cause Open access disruptions in health and healthcare. [8][9][10] In this analysis, we also find evidence that such mobility is also associated with reduced routine care utilisation in children with a chronic disease. From these findings we are unable to determine if these children received sufficient or quality care, but the fact that they use less than their counterparts raises concern that this is possible, and clinical organisations and future research could consider further evaluating risk screening strategies that employ number of address changes from administrative data in order to stratify clinical risk.…”

Section: Open Accesssupporting

confidence: 55%

“…A Welsh team, using data from more than 200 000 children, found that moving within the first year of life was associated with increased risk of future emergency hospitalisation for asthma. 8 Other studies from Europe and New Zealand have also found residential mobility to be associated with negative health outcomes 9 10 possibly because moves can be an indication of financial insecurity or other underlying family instability.…”

Section: Introductionmentioning

confidence: 99%

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Mobility and social deprivation on primary care utilisation among paediatric patients with asthma

et al. 2021

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ObjectiveAsthma care is negatively impacted by neighbourhood social and environmental factors, and moving is associated with undesirable asthma outcomes. However, little is known about how movement into and living in areas of high deprivation relate to primary care use. We examined associations between neighbourhood characteristics, mobility and primary care utilisation of children with asthma to explore the relevance of these social factors in a primary care setting.DesignIn this cohort study, we conducted negative binomial regression to examine the rates of primary care visits and annual influenza vaccination and logistic regression to study receipt of pneumococcal vaccination. All models were adjusted for patient-level covariates.SettingWe used data from community health centres in 15 OCHIN states.ParticipantsThe sample included 23 773 children with asthma aged 3–17 across neighbourhoods with different levels of social deprivation from 2012 to 2017. We conducted negative binomial regression to examine the rates of primary care visits and annual influenza vaccination and logistic regression to study receipt of pneumococcal vaccination. All models were adjusted for patient-level covariates.ResultsClinic visit rates were higher among children living in or moving to areas with higher deprivation than those living in areas with low deprivation (rate ratio (RR) 1.09, 95% CI 1.02 to 1.17; RR 1.05, 95% CI 1.00 to 1.11). Children moving across neighbourhoods with similarly high levels of deprivation had increased RRs of influenza vaccination (RR 1.13, 95% CI 1.03 to 1.23) than those who moved but stayed in neighbourhoods of low deprivation.ConclusionsMovement into and living within areas of high deprivation is associated with more primary care use, and presumably greater opportunity to reduce undesirable asthma outcomes. These results highlight the need to attend to patient movement in primary care visits, and increase neighbourhood-targeted population management to improve equity and care for children with asthma.

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Section: Open Accesssupporting

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Mobility and social deprivation on primary care utilisation among paediatric patients with asthma

et al. 2021

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“…Our previous work indicated that ≥ 2 home moves for young children were associated with an increased risk of emergency admissions (IRR 1.33, 95% CI 1.18 to 1.51). 53 Therefore, this may be an indication of moving into an unfamiliar home, as opposed to related to the garden paths themselves.…”

Section: The Effect Of the Housing Intervention On Other Health Outcomesmentioning

confidence: 99%

Health impact, and economic value, of meeting housing quality standards: a retrospective longitudinal data linkage study

et al. 2018

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BackgroundPoor-quality housing adversely affects residents’ health but there is a paucity of high-quality evidence to support this.ObjectiveThis research investigated the health impact of bringing housing to a national quality standard.DesignA natural experiment of improvements to housing quality analysed using repeated measures of health-care utilisation and economic outcomes at an individual person level.SettingCarmarthenshire, UK.ParticipantsA total of 32,009 residents registered for a minimum of 60 days at 8558 social homes that received housing improvements between January 2005 and March 2015.InterventionsMultiple internal and external housing improvements, including wall and loft insulation, windows and doors, heating system upgrades, new kitchens and bathrooms, garden path safety improvements and electrical system upgrades (adding power sockets, and extractor fans in kitchens and bathrooms).Main outcome measuresEmergency hospital admissions for cardiorespiratory conditions and injuries. Primary health-care utilisation for respiratory and common mental health disorders, emergency department injury attendances and health-care utilisation costs.Data sourcesCarmarthenshire County Council home address and intervention records were anonymously linked within the Secure Anonymous Information Linkage databank to demographic information from the Welsh Demographic Service data set; hospital admission data from the Patient Episode Dataset for Wales; primary care contacts and prescribed medications from general practice data; emergency department attendances from the Emergency Department Data Set; and deaths from the Office for National Statistics mortality register.MethodsThe study used a longitudinal panel design to examine changes in standard of eight housing cointervention from intervention records, and linked to individuals registered at intervention homes. Health outcomes were obtained retrospectively for each individual in a dynamic cohort and were captured for up to 123 consecutive months. An additional local authority region could not be utilised as a comparator owing to different reporting pressures resulting in the recording of a different intervention. The exposure group for each cointervention was compared with an internal reference group of people living in homes that did not receive the cointervention during their tenancy. A multilevel modelling approach was used to account for repeated observations for individuals living in intervention homes. Counts of health outcomes were analysed using negative binomial regression models to determine the effect of each cointervention that reached housing quality standards during an individual’s period of tenancy, compared with those living in properties that did not. We adjusted for potential confounding factors and for background trends in the regional general population. A cost–consequences analysis was conducted as part of the health economic evaluation.ResultsResidents aged ≥ 60 years living in homes in which electrical systems were upgraded were associated with 39% fewer admissions than those living in homes in which they were not [incidence rate ratio (IRR) 0.61, 95% confidence interval (CI) 0.53 to 0.72;p < 0.01]. Reduced admissions were also associated with windows and doors (IRR 0.71, 95% CI 0.63 to 0.81;p < 0.01), wall insulation (IRR 0.75, 95% CI 0.67 to 0.84;p < 0.01) and gardens and estates (IRR 0.73, 95% CI 0.64 to 0.83;p < 0.01) for those living in homes in which these cointervention were upgraded. There were no associations of change in emergency admissions with upgrading heating (IRR 0.91, 95% CI 0.82 to 1.01;p = 0.072), loft insulation (IRR 0.98, 95% CI 0.86 to 1.11;p = 0.695), kitchens (IRR 0.98, 95% CI 0.83 to 1.17;p = 0.843) or bathrooms (IRR 0.93, 95% CI 0.81 to 1.06;p = 0.287).LimitationsThere was no randomisation, there were incomplete data on the scale of the intervention for individual households and there were no estimates for the impact of the whole programme.ConclusionsThis complex interdisciplinary study found that hospital admissions could be avoided through improving housing quality standards.Future workAt their initiation, future non-health projects should have a built-in evaluation to allow intervention exposures to be randomly allocated to residents, with the simultaneous analysis of multiple health outcomes in one statistical model.FundingThe National Institute for Health Research Public Health Research programme.

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“…This complex cohort enables numerous research questions to be addressed. For example, WECC has revealed factors that increase the likelihood of respiratory admissions up to age 5 years; and that children who move house frequently have an increased risk of poor health and educational underachievement [34][35][36].…”

Section: Noteworthy Outputsmentioning

confidence: 99%

A Profile of the SAIL Databank on the UK Secure Research Platform

Jones

Ford

Thompson

et al. 2020

IJPDS

111

128

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Background The Secure Anonymised Information Linkage (SAIL) Databank is a national data safe haven of de‑identified datasets principally about the population of Wales, made available in anonymised form to researchers across the world. It was established to enable the vast arrays of data collected about individuals in the course of health and other public service delivery to be made available to answer important questions that could not otherwise be addressed without prohibitive effort. The SAIL Databank is the bedrock of other funded centres relying on the data for research. Approach SAIL is a data repository surrounded by a suite of physical, technical and procedural control measures embodying a proportionate privacy-by-design governance model, informed by public engagement, to safeguard the data and facilitate data utility. SAIL operates on the UK Secure Research Platform (SeRP), which is a customisable technology and analysis platform. Researchers access anonymised data via this secure research environment, from which results can be released following scrutiny for disclosure risk. SAIL data are being used in multiple research areas to evaluate the impact of health and social exposures and policy interventions. Discussion Lessons learned and their applications include: managing evolving legislative and regulatory requirements; employing multiple, tiered security mechanisms; working hard to increase analytical capacity efficiency; and developing a multi-faceted programme of public engagement. Further work includes: incorporating new data types; enabling alternative means of data access; and developing further efficiencies across our operations. Conclusion SAIL represents an ongoing programme of work to develop and maintain an extensive, whole population data resource for research. Its privacy-by-design model and UK SeRP technology have received international acclaim, and we continually endeavour to demonstrate trustworthiness to support data provider assurance and public acceptability in data use. We strive for further improvement and continue a mutual learning process with our contemporaries in this rapidly developing field.

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Residential Moving and Preventable Hospitalizations

Cited by 11 publications

References 32 publications

Mobility and social deprivation on primary care utilisation among paediatric patients with asthma

Mobility and social deprivation on primary care utilisation among paediatric patients with asthma

Health impact, and economic value, of meeting housing quality standards: a retrospective longitudinal data linkage study

A Profile of the SAIL Databank on the UK Secure Research Platform

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