Suchergebnisse

Improved availability of population-based data via data linkage enables researchers to develop deeper insight into racial health inequities in the UK. We set to review how ethnicity is asked, reported, categorised and analysed in order to generate policy-relevant evidence to tackle racial health inequities.
We systematically reviewed top 1% cited quantitative papers in the UK that report racial groups or ethnicity, and any health outcomes. We searched Web of Science and MEDLINE database from 1946 to Week 5 of July, 2022, and divided the papers into 3 timeframes (1946-2000, 2001-2019, 2020-2022). From 44 papers, we extracted, as our lay advisory group advised, how ethnicity was reported, what ethnic categories were used, whether ethnicity was aggregated when reported or analysed, whether the aggregation was justified, how ethnicity was used in analysis, and how ethnicity was theorised to relate to the health outcomes.
Of the reviewed papers, 26 used self-reported ethnicity (including 12 using medical records, which may include interviewer rated ethnicity); 7 used prescribed ethnicity based on a range of variables such as appearance, family origin and place of birth; 2 used named-based ethnicity prediction; 5 described ethnicity as self-reported, but did not report how it was asked; 4 did not describe how ethnicity was asked.
Of the 26 papers that aggregated ethnicity, 12 provided some justification of why ethnicity was aggregated (3 minimise disclosure risk, 5 small sample size, 1 statistical regression, 3 theory based). Only 9 papers explicitly theorised the role of ethnicity in their analysis, and how it related to the relevant health outcomes. Missing, mixed or other ethnicity were treated variably across studies.
Ethnicity is a multi-dimensional construct. Researchers should communicate clearly how ethnicity is operationalised for their studies, with appropriate justification for clustering and analysis that is meaningfully theorised. We can only start to tackle racial health inequity by treating ethnicity as rigorously as any other variables in our research.

BACKGROUND: Homelessness is a global issue and HIV, hepatitis C and tuberculosis are known to be prevalent in this group. Homeless populations face significant barriers to care. We aim to summarise evidence of treatment initiation and completion for homeless populations with these infections, and their associated factors, through a systematic review and meta-analysis. METHODS: We will search MEDLINE, Embase and CINAHL for all study types and conference abstracts looking at either (1) treatment initiation in a cohort experiencing homelessness with at least one of HIV, hepatitis C, active tuberculosis and/or latent tuberculosis infection (LTBI); (2) treatment completion for those who initiated treatment. We will perform a meta-analysis of the proportion of those with each infection who initiate and complete treatment, as well as analysis of individual and health system factors that may affect adherence levels. We will evaluate the quality of research papers using the Newcastle-Ottawa scale. DISCUSSION: Given the political emphasis on global elimination of these diseases, and the current lack of understanding of effective and equitable treatment adherence strategies in homeless populations, this review will provide insight to policy-makers and service providers aiming to improve homeless healthcare. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42019153150

IntroductionIn England, details on hospital admissions and mortality are recorded nationally, but housing status and patients' hospital discharge arrangements are only recorded locally within discharge services. These data are required to evaluate specialist homeless hospital discharge (HHD) services in England, and can be obtained through linkage within and across sectors.
Objectives and ApproachWe aimed to improve linkage to enable the evaluation of HHD schemes. 16 sites with a scheme were recruited along with a specialist facility that deliver screening and treatment services to homeless hostels (Find\&Treat). Linkage fields including National Health Service number (NHS number), name, gender and birthdate for clinical contacts between November 2013 and November 2016 were collected and linked to national hospital data, Hospital Episodes Statistics (HES). To improve linkage with HES, intermediate-linkage to a gender-names dictionary and a national demographic database (NDD) was performed. Ethics, access permissions were obtained through HRA-REC (REC16/EE/0018) and NHS CAG (16/CAG/0021).
Results47,569 clinical contacts among people who were homeless were collected from Find&Treat and 12,931 from sites. The median age at mid-study period (15th May 2015) among contacts with sites compared to Find&Treat were similar at 44 (IQR 34-53, n=12,905) and 45 (IQR 35-54, n=47,569), respectively. Among Find&Treat, 82% (n=38,905) were contacts with Males and 18% (n=8,650) with Females. Gender was not collected at all HHD sites or for all admissions. 70% of contacts had missing gender and among these contacts, gender was assigned using the gender-names dictionary. After imputing gender, 52% of contacts all linkage fields and 47% had all but NHS number. These data were linked to the NDD, an approximate 60% linkage rate was achieved retrieving complete linkage fields for these contacts.
Conclusion/ImplicationsIntermediate linkage steps described here provides the largest dataset of it's kind, enabling investigations into effectiveness of hospital discharge schemes in England. The study provides generally a proof of concept that large cohorts of hard-to-reach population groups can be obtained through data linkage.