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Background: Universal health visiting has been a cornerstone of preventative healthcare for children in the United Kingdom (UK) for over 100 years. In 2016, Scotland introduced a new Universal Health Visiting Pathway (UHVP), involving a greater number of contacts with a particular emphasis on the first year, visits within the home setting, and rigorous developmental assessment conducted by a qualified Health Visitor. To evaluate the UHVP, an outcome indicator framework was developed using routine administrative data. This paper sets out the development of these indicators. Methods: A logic model was produced with stakeholders to define the group of outcomes, before further refining and aligning of the measures through discussions with stakeholders and inspection of data. Power calculations were carried out and initial data described for the chosen indicators. Results: Eighteen indicators were selected across eight outcome areas: parental smoking, breastfeeding, immunisations, dental health, developmental concerns, obesity, accidents and injuries, and child protection interventions. Data quality was mixed. Coverage of reviews was high; over 90% of children received key reviews. Individual item completion was more variable: 92.2% had breastfeeding data at 6–8 weeks, whilst 63.2% had BMI recorded at 27–30 months. Prevalence also varied greatly, from 1.3% of children's names being on the Child Protection register for over six months by age three, to 93.6% having received all immunisations by age two. Conclusions: Home visiting services play a key role in ensuring children and families have the right support to enable the best start in life. As these programmes evolve, it is crucial to understand whether changes lead to improvements in child outcomes. This paper describes a set of indicators using routinely-collected data, lessening additional burden on participants, and reducing response bias which may be apparent in other forms of evaluation. Further research is needed to explore the transferability of this indicator framework to other settings. [ABSTRACT FROM AUTHOR]

Background: The ethnicity data gap pertains to 3 major challenges to address ethnic health inequality: 1) Under-representation of ethnic minorities in research; 2) Poor data quality on ethnicity; 3) Ethnicity data not being meaningfully analysed. These challenges are especially relevant for research involving under-served migrant populations in the UK. We aimed to review how ethnicity is captured, reported, analysed and theorised within policy-relevant research on ethnic health inequities. Methods: We reviewed a selection of the 1% most highly cited population health papers that reported UK data on ethnicity, and extracted how ethnicity was recorded and analysed in relation to health outcomes. We focused on how ethnicity was obtained (i.e. self reported or not), how ethnic groups were categorised, whether justification was provided for any categorisation, and how ethnicity was theorised to be related to health. We held three 1-h-long guided focus groups with 10 young people from Nigeria, Turkistan, Syria, Yemen and Iran. This engagement helped us shape and interpret our findings, and reflect on. 1) How should ethnicity be asked inclusively, and better recorded? 2) Does self-defined ethnicity change over time or context? If so, why? Results: Of the 44 included papers, most (19; 43%) used self-reported ethnicity, categorised in a variety of ways. Of the 27 papers that aggregated ethnicity, 13 (48%) provided justification. Only 8 of 33 papers explicitly theorised how ethnicity related to health. The focus groups agreed that 1) Ethnicity should not be prescribed by others; individuals could be asked to describe their ethnicity in free-text which researchers could synthesise to extract relevant dimensions of ethnicity for their research; 2) Ethnicity changes over time and context according to personal experience, social pressure, and nationality change; 3) Migrants and non-migrants' lived experience of ethnicity is not fully inter-changeable, even if they share the same ethnic category. Conclusions: Ethnicity is a multi-dimensional construct, but this is not currently reflected in UK health research studies, where ethnicity is often aggregated and analysed without justification. Researchers should communicate clearly how ethnicity is operationalised for their study, with appropriate justification for clustering and analysis that is meaningfully theorised. We can only start to tackle ethnic health inequity by treating ethnicity as rigorously as any other variables in our research. [ABSTRACT FROM AUTHOR]

Introduction: Several forces are contributing to an increase in the number of people living with and surviving colorectal cancer (CRC). However, due to the lack of available data, little is known about the implications of these forces. In recent years, the use of administrative records to inform research has been increasing. The aim of this paper is to investigate the potential contribution that administrative data could have on the health economic research of CRC. Methods: To achieve this aim, we conducted a systematic review of the health economic CRC literature published in the United Kingdom and Europe within the last decade (2009–2019). Results: Thirty‐seven relevant studies were identified and divided into economic evaluations, cost of illness studies and cost consequence analyses. Conclusions: The use of administrative data, including cancer registry, screening and hospital records, within the health economic research of CRC is commonplace. However, we found that this data often come from regional databases, which reduces the generalisability of results. Further, administrative data appear less able to contribute towards understanding the wider and indirect costs associated with the disease. We explore several ways in which various sources of administrative data could enhance future research in this area. [ABSTRACT FROM AUTHOR]