Ethnic inequalities in age-related patterns of multiple long-term conditions in England: Analysis of primary care and nationally representative survey data.

Little is known about the patterning of multiple long-term conditions (MLTCs) by age, ethnicity and across conceptualisations of MLTCs (e.g. MLTCs with/without mental health conditions [MHCs]). We examined ethnic inequalities in age-related patterns of MLTCs, and combinations of physical and MHCs using the English GP Patient Survey and Clinical Practice Research Datalink. We described the association between MLTCs and age using multilevel regression models adjusting for sex and area-level deprivation with patients nested within GP practices. Similar analyses were repeated for MLTCs that include MHCs. We observed ethnic inequalities from middle-age onwards such as older Pakistani, Indian, Black Caribbean and Other ethnic people had increased risk of MLTCs compared to white British people, even after adjusting for area-level deprivation. Compared to white British people, Gypsy and Irish Travellers had higher levels of MLTCs across the age groups, and Chinese people had lower levels. Pakistani and Bangladeshi people aged 50-74 years were more likely than white people to report MLTCs that included MHCs. We find clear evidence of ethnic inequalities in MLTCs. The lower prevalence of MLTCs that include MHCs among some minoritised ethnic groups may be an underestimation due to underdiagnosis and/or inadequate primary care and requires further scrutiny.

Ethnic inequities in the patterns of personalized care adjustments for 'informed dissent' and 'patient unsuitable': a retrospective study using Clinical Practice Research Datalink.

BACKGROUND: In England, general practitioners voluntarily take part in the Quality and Outcomes Framework, which is a program that seeks to improve care by rewarding good practice. They can make personalized care adjustments (PCAs), e.g. if patients choose not to have the treatment/intervention offered ('informed dissent') or because they are considered to be clinically 'unsuitable'. METHODS: Using data from the Clinical Practice Research Datalink (Aurum), this study examined patterns of PCA reporting for 'informed dissent' and 'patient unsuitable', how they vary across ethnic groups and whether ethnic inequities were explained by sociodemographic factors or co-morbidities. RESULTS: The odds of having a PCA record for 'informed dissent' were lower for 7 of the 10 minoritized ethnic groups studied. Indian patients were less likely than white patients to have a PCA record for 'patient unsuitable'. The higher likelihood of reporting for 'patient unsuitable' among people from Black Caribbean, Black Other, Pakistani and other ethnic groups was explained by co-morbidities and/or area-level deprivation. CONCLUSIONS: The findings counter narratives that suggest that people from minoritized ethnic groups often refuse medical intervention/treatment. The findings also illustrate ethnic inequities in PCA reporting for 'patient unsuitable', which are linked to clinical and social complexity and should be tackled to improve health outcomes for all.

Ethnic inequalities in multiple long-term health conditions in the United Kingdom: a systematic review and narrative synthesis.

Indicative evidence suggests that minoritised ethnic groups have higher risk of developing multiple long-term conditions (MLTCs), and do so earlier than the majority white population. While there is evidence on ethnic inequalities in single health conditions and comorbidities, no review has attempted to look across these from a MLTCs perspective. As such, we currently have an incomplete understanding of the extent of ethnic inequalities in the prevalence of MLTCs. Further, concerns have been raised about variations in the way ethnicity is operationalised and how this impedes our understanding of health inequalities. In this systematic review we aimed to 1) describe the literature that provides evidence of ethnicity and prevalence of MLTCs amongst people living in the UK, 2) summarise the prevalence estimates of MLTCs across ethnic groups and 3) to assess the ways in which ethnicity is conceptualised and operationalised. We focus on the state of the evidence prior to, and during the very early stages of the pandemic. We registered the protocol on PROSPERO (CRD42020218061). Between October and December 2020, we searched ASSIA, Cochrane Library, EMBASE, MEDLINE, PsycINFO, PubMed, ScienceDirect, Scopus, Web of Science, OpenGrey, and reference lists of key studies/reviews. The main outcome was prevalence estimates for MLTCs for at least one minoritised ethnic group, compared to the majority white population. We included studies conducted in the UK reporting on ethnicity and prevalence of MLTCs. To summarise the prevalence estimates of MLTCs across ethnic groups we included only studies of MLTCs that provided estimates adjusted at least for age. Two reviewers screened and extracted data from a random sample of studies (10%). Data were synthesised using narrative synthesis. Of the 7949 studies identified, 84 met criteria for inclusion. Of these, seven contributed to the evidence of ethnic inequalities in MLTCs. Five of the seven studies point to higher prevalence of MLTCs in at least one minoritised ethnic group compared to their white counterparts. Because the number/types of health conditions varied between studies and some ethnic populations were aggregated or omitted, the findings may not accurately reflect the true level of ethnic inequality. Future research should consider key explanatory factors, including those at the macrolevel (e.g. racism, discrimination), as they may play a role in the development and severity of MLTCs in different ethnic groups. Research is also needed to ascertain the extent to which the COVID19 pandemic has exacerbated these inequalities.

Continuity of care in diverse ethnic groups: a general practice record study in England.

BACKGROUND: GPs and patients value continuity of care. Ethnic differences in continuity could contribute to inequalities in experience and outcomes. AIM: To describe relational continuity of care in general practice by ethnicity and long-term conditions. DESIGN AND SETTING: In total, 381 474 patients in England were included from a random sample from the Clinical Practice Research Datalink (January 2016 to December 2019). METHOD: Face-to-face, telephone, and online consultations with a GP were included. Continuity, measured by the Usual Provider of Care and Bice-Boxerman indices, was calculated for patients with ≥3 consultations. Ethnicity was taken from the GP record or linked Hospital Episode Statistics data, and long-term conditions were counted at baseline. Multilevel regression models were used to describe continuity by ethnicity sequentially adjusted for: a) the number of consultations, follow-up time, age, sex, and practice-level random intercept; b) socioeconomic deprivation in the patient's residential area; and c) long-term conditions. RESULTS: On full adjustment, 5 of 10 ethnic minority groups (Bangladeshi, Pakistani, Black African, Black Caribbean, and any other Black background) had lower continuity of care compared with White patients. Continuity was lower for patients in more deprived areas and younger patients but this did not account for ethnic differences in continuity. Differences by ethnicity were also seen in patients with ≥2 long-term conditions. CONCLUSION: Ethnic minority identity and socioeconomic deprivation have additive associations with lower continuity of care. Structural factors affecting demand for, and supply of, GPs should be assessed for their contribution to ethnic inequalities in relational continuity and other care quality domains.

Ethnic Inequalities in Healthcare Use and Care Quality among People with Multiple Long-Term Health Conditions Living in the United Kingdom: A Systematic Review and Narrative Synthesis.

Indicative evidence suggests that the prevalence of multiple long-term conditions (i.e., conditions that cannot be cured but can be managed with medication and other treatments) may be higher in people from minoritised ethnic groups when compared to people from the White majority population. Some studies also suggest that there are ethnic inequalities in healthcare use and care quality among people with multiple long-term conditions (MLTCs). The aims of this review are to (1) identify and describe the literature that reports on ethnicity and healthcare use and care quality among people with MLTCs in the UK and (2) examine how healthcare use and/or care quality for people with MLTCs compares across ethnic groups. We registered the protocol on PROSPERO (CRD42020220702). We searched the following databases up to December 2020: ASSIA, Cochrane Library, EMBASE, MEDLINE, PsycINFO, PubMed, ScienceDirect, Scopus, and Web of Science core collection. Reference lists of key articles were also hand-searched for relevant studies. The outcomes of interest were patterns of healthcare use and care quality among people with MLTCs for at least one minoritised ethnic group, compared to the White majority population in the UK. Two reviewers, L.B. and B.H., screened and extracted data from a random sample of studies (10%). B.H. independently screened and extracted data from the remaining studies. Of the 718 studies identified, 14 were eligible for inclusion. There was evidence indicating ethnic inequalities in disease management and emergency admissions among people with MLTCs in the five studies that counted more than two long-term conditions. Compared to their White counterparts, Black and Asian children and young people had higher rates of emergency admissions. Black and South Asian people were found to have suboptimal disease management compared to other ethnic groups. The findings suggest that for some minoritised ethnic group people with MLTCs there may be inadequate initiatives for managing health conditions and/or a need for enhanced strategies to reduce ethnic inequalities in healthcare. However, the few studies identified focused on a variety of conditions across different domains of healthcare use, and many of these studies used broad ethnic group categories. As such, further research focusing on MLTCs and using expanded ethnic categories in data collection is needed.