Measuring disadvantage in the early years in the UK: A systematic scoping review.

Background: The relationship between disadvantage and child health in the early years is well established. For this evidence base to most helpfully inform services, we need to better understand how disadvantage is conceptualised and measured in the literature. We aimed to conceptualise disadvantage measured in child health literature and explore the associations between disadvantage and child health using these measures. Method: We conducted a scoping review using systematic methods to identify key concepts of disadvantage used in empirical child health literature. We searched MEDLINE, Scopus, and grey literature for studies exploring the association between disadvantage and child health outcomes for children aged 0-5 in the United Kingdom. We extracted and analysed data from 86 studies. Results: We developed a framework describing two domains, each with two attributes conceptualising disadvantage: level of disadvantage indicator (individual and area) and content of disadvantage indicator (social and economic). Individual-level measures of disadvantage tended to identify stronger associations between disadvantage and child health compared with area-level measures. Conclusion: The choice of disadvantage indicators, particularly whether individual- or area-level, can affect the inferences made about the relationship between disadvantage and child health. Better access to individual-level disadvantage indicators in administrative data could support development and implementation of interventions aimed at reducing child health inequalities in the early years.

Explaining local variation in referrals from health services to children's social care in England 2013-16: a study using 'children in need' administrative data.

BACKGROUND: Referral rates from Health service to Children's Social Care (CSC) services vary across England. In 2019, the National Audit Office (re)iterated the urgent need to understand the drivers of such variation. METHODS: Using administrative data (Children in Need Census, 2013-16), we calculated annual referral rates from Health to CSC services (Health referral rate) by Local Authority (LA) areas. We used multilevel linear regression to investigate the relationship between age-adjusted Health referral rates and local need (demand factors) and local practice/systems (supply factors). We present a tool to compare unadjusted and adjusted LA rates. RESULTS: There was high LA variation in Health referral rates, particularly for infants (mean = 29.0/1000 children < 1 y; range = 6.5-101.8; sd = 12.4). LA variation persisted after age-adjustment. Child poverty (local need) and overall referral rate (local practice/systems) explained 60% of variation in age-adjusted Health referral rates. Overall referral rate was the strongest predictor. Adjusted referral rates were substantially different from unadjusted rates. After adjustment, 57.7% of LAs had higher/lower Health referral rates than expected. CONCLUSIONS: While higher levels of local need are associated with higher Health referrals, some areas have high Health referrals irrespective of local need. Our tool demonstrates the benefits of using adjusted rates to compare LAs.

Prevalence of Down's Syndrome in England, 1998-2013: Comparison of linked surveillance data and electronic health records.

INTRODUCTION: Disease registers and electronic health records are valuable resources for disease surveillance and research but can be limited by variation in data quality over time. Quality may be limited in terms of the accuracy of clinical information, of the internal linkage that supports person-based analysis of most administrative datasets, or by errors in linkage between multiple datasets. OBJECTIVES: By linking the National Down Syndrome Cytogenetic Register (NDSCR) to Hospital Episode Statistics for England (HES), we aimed to assess the quality of each and establish a consistent approach for analysis of trends in prevalence of Down's syndrome among live births in England. METHODS: Probabilistic record linkage of NDSCR to HES for the period 1998-2013 was supported by linkage of babies to mothers within HES. Comparison of prevalence estimates in England were made using NDSCR only, HES data only, and linked data. Capture-recapture analysis and quantitative bias analysis were used to account for potential errors, including false positive diagnostic codes, unrecorded diagnoses, and linkage error. RESULTS: Analyses of single-source data indicated increasing live birth prevalence of Down's Syndrome, particularly in the analysis of HES. Linked data indicated a contrastingly stable prevalence of 12.3 (plausible range: 11.6-12.7) cases per 10 000 live births. CONCLUSION: Case ascertainment in NDSCR improved slightly over time, creating a picture of slowly increasing prevalence. The emerging epidemic suggested by HES primarily reflects improving linkage within HES (assignment of unique patient identifiers to hospital episodes). Administrative data are valuable but trends should be interpreted with caution, and with assessment of data quality over time. Data linkage with quantitative bias analysis can provide more robust estimation and, in this case, stronger evidence that prevalence is not increasing. Routine linkage of administrative and register data can enhance the value of each.

Demystifying probabilistic linkage: Common myths and misconceptions.

Many of the distinctions made between probabilistic and deterministic linkage are misleading. While these two approaches to record linkage operate in different ways and can produce different outputs, the distinctions between them are more a result of how they are implemented than because of any intrinsic differences. In the way they are generally applied, probabilistic and deterministic procedures can be little more than alternative means to similar ends-or they can arrive at very different ends depending on choices that are made during implementation. Misconceptions about probabilistic linkage contribute to reluctance for implementing it and mistrust of its outputs. We aim to explain how the outputs of either approach can be tailored to suit the intended application, but also to highlight the ways in which probabilistic linkage is generally more flexible, more powerful and more informed by the data. This is accomplished by examining common misconceptions about probabilistic linkage and its difference from deterministic linkage, highlighting the potential impact of design choices on the outputs of either approach. We hope that better understanding of linkage designs will help to allay concerns about probabilistic linkage, and help data linkers to select and tailor procedures to produce outputs that are appropriate for their intended use.

Using the RECORD guidelines to improve transparent reporting of studies based on routinely collected data.

Transparent reporting of routinely-collected data studies is key to producing valid and reliable research that can inform decisions about patient care and health systems. This article discusses some of the unique challenges in using these data sources, and explains how the REporting of studies Conducted using Observational Routinely-collected Data (RECORD) guidelines were developed to help researchers and journals to maintain a high level of quality in reporting of healthcare studies using routinely-collected data.

The clinical, occupational and financial outcomes associated with a bespoke specialist clinic for military aircrew-a cohort study.

OBJECTIVES: To assess the clinical, occupational and financial outcomes of a new Clinical Aviation Medicine Service (CAMS) for UK military personnel. METHODS: Consecutive patients over a 2 year period were included. Predictors of flying restrictions at referral and final outcome following consultation were modelled using logistic regression. National Health Service (NHS) Payment by Results tariffs and Defence capitation data were used to assess the financial impact of the service. RESULTS: Eight hundred and sixteen new referrals (94.5% male, median age 45 years (range 19-75)) were received and 1025 consultations performed. Cardiovascular disease was the commonest reason for referral. CAMS clinical activity cost at NHS tariff was £453 310 representing a saving of £316 173 (£137 137 delivery cost). In total, 310/816 (38%) patients had employment restrictions on referral and 49.0% of this group returned to full employment following their initial consultation. Compared with cardiology, general medicine and respiratory patients were more likely to have been occupationally restricted prior to referral (50 vs. 35%, OR 1.81; 95% CI 1.18-2.76, P values=0.006 and 53 vs. 35%, OR 2.12; 95% CI 1.15-3.90, P values = 0.016, respectively). Overall 581/816 (71.2%) of patients returned to unrestricted employment while 98/816 (12.0%) were unable to continue in any aircrew role. The service saved 7000 lost working days per year at an estimated occupational saving of ∼£1 million per annum. CONCLUSIONS: This bespoke service has allowed rapid, occupationally relevant clinical care to be delivered with both time and financial savings. The model may have significant occupational and financial relevance for other environmental and occupational medical organizations.

Incidence rate trends in childhood type 1 diabetes in Yorkshire, UK 1978-2007: effects of deprivation and age at diagnosis in the South Asian and non-South Asian populations.

AIMS: Incidence of Type 1 diabetes in children is increasing worldwide. Earlier studies suggest that UK south Asian immigrants develop similar rates to the overall UK population, although incidence is lower in their country of origin. This study examines incidence rate trends of childhood Type 1 diabetes in Yorkshire 1978-2007, focusing on differences between south Asians and non-south Asians. METHODS: Data from the population-based Yorkshire Register of Diabetes in Children and Young People were used to estimate incidence (per 100,000 childhood population < 15 years per year) of Type 1 diabetes, stratified by sex, age and ethnicity validated using two name-recognition programs. Age-sex standardized rates were calculated for 1978-2007 and assessed by ethnic-group and deprivation for 1990-2007. We used Poisson regression to assess incidence trends and predict rates until 2020. RESULTS: From 1978-2007, 3912 children were diagnosed. Overall incidence was 18.1 per 100,000 childhood population (< 15 years) per year (95% CI17.6-18.7) and increased significantly over time: 13.2 (1978-1987) to 17.3 (1988-1997) to 24.2 (1998-2007). Average annual percentage change was 2.8% (2.5-3.2). Incidence for non-south Asians (21.5; 20.7-22.4) was significantly higher than for south Asians (14.7; 12.4-17.1). Average annual percentage change increased significantly over 18 years (1990-2007) in non-south Asians (3.4%; 2.7-4.2) compared with a non-significant rise of 1.5% (-1.5 to 4.6) in south Asians. Deprivation score did not affect overall incidence. CONCLUSIONS: Type 1 diabetes incidence rose almost uniformly for non-south Asians, but not for south Asians, contrary to previous studies. Overall rates are predicted to rise by 52% from 2007 to 2020 to 39.0 per 100,000 per year.