The association between ethnicity and delay in seeking medical care for chest pain

Wechkunanukul, Kannikar; Grantham, Hugh; Damarell, Raechel; Clark, Robyn

doi:10.11124/jbisrir-2016-003012

Cited by 20 publications

(22 citation statements)

References 72 publications

(144 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…29 32 33 Some researchers have postulated that ethnic inequalities may be associated with decreased symptom recognition and poor engagement with health services. 34 However, while frequency of ICU admission, AKI and need for mechanical ventilation suggests more severe peak disease in minority ethnic groups, time to ICU admission did not differ and differences in first total NEWS were at most modest, suggesting against a large effect from delayed presentation.…”

Section: Discussionmentioning

confidence: 91%

Ethnicity and outcomes in patients hospitalised with COVID-19 infection in East London: an observational cohort study

et al. 2021

View full text Add to dashboard Cite

ObjectiveTo describe outcomes within different ethnic groups of a cohort of hospitalised patients with confirmed COVID-19 infection. To quantify and describe the impact of a number of prognostic factors, including frailty and inflammatory markers.SettingFive acute National Health Service Hospitals in east London.DesignProspectively defined observational study using registry data.Participants1737 patients aged 16 years or over admitted to hospital with confirmed COVID-19 infection between 1 January and 13 May 2020.Main outcome measuresThe primary outcome was 30-day mortality from time of first hospital admission with COVID-19 diagnosis during or prior to admission. Secondary outcomes were 90-day mortality, intensive care unit (ICU) admission, ICU and hospital length of stay and type and duration of organ support. Multivariable survival analyses were adjusted for potential confounders.Results1737 were included in our analysis of whom 511 had died by day 30 (29%). 538 (31%) were from Asian, 340 (20%) black and 707 (40%) white backgrounds. Compared with white patients, those from minority ethnic backgrounds were younger, with differing comorbidity profiles and less frailty. Asian and black patients were more likely to be admitted to ICU and to receive invasive ventilation (OR 1.54, (95% CI 1.06 to 2.23); p=0.023 and OR 1.80 (95% CI 1.20 to 2.71); p=0.005, respectively). After adjustment for age and sex, patients from Asian (HR 1.49 (95% CI 1.19 to 1.86); p<0.001) and black (HR 1.30 (95% CI 1.02 to 1.65); p=0.036) backgrounds were more likely to die. These findings persisted across a range of risk factor-adjusted analyses accounting for major comorbidities, obesity, smoking, frailty and ABO blood group.ConclusionsPatients from Asian and black backgrounds had higher mortality from COVID-19 infection despite controlling for all previously identified confounders and frailty. Higher rates of invasive ventilation indicate greater acute disease severity. Our analyses suggest that patients of Asian and black backgrounds suffered disproportionate rates of premature death from COVID-19.

show abstract

Section: Discussionmentioning

confidence: 91%

Ethnicity and outcomes in patients hospitalised with COVID-19 infection in East London: an observational cohort study

et al. 2021

View full text Add to dashboard Cite

show abstract

“…A systematic review is useful for determining ways of improving Australian government services and systems (Klassen et al, 2010) including how to better meet the needs of refugees and migrants from culturally and linguistically diverse backgrounds (Wechkunanukul, Grantham, Damarell, & Clark, 2016). This systematic review synthesises available evidence to assist policymakers, practitioners and researchers to make decisions for developing, implementing, evaluating and performing translation activities that use information technology.…”

Section: Methodsmentioning

confidence: 99%

Do multilingual androids dream of a better life in Australia? Effectiveness of information technology for government translation to support refugees and migrants in Australia

O’Mara

Carey

2019

Aust J Public Adm

View full text Add to dashboard Cite

Without high‐quality translation of online information about government support and services, refugees and migrants from culturally and linguistically diverse backgrounds in Australia experience a major barrier to improved health, employment, education and social outcomes. Recent advances in the ability of Google Translate, Skype Translator and other forms of machine translation that use artificial intelligence can help translate government information to better support refugees and migrants but they bring the risk of ineffective communication, and exclusion from services that could positively impact on settlement experiences and daily life. Evidence suggests that government agencies are likely to be using human translators for most translation work, but the degree to which any form of information technology is used, how it may be best applied and the associated effects are not known. This study systematically reviewed the peer‐reviewed and grey literature to determine effective ways of using information technology for translating government information to refugees and migrants from culturally and linguistically diverse backgrounds in Australia. Included studies were analysed to identify techniques and other characteristics of translation, information technology and language support more broadly, and outcomes on education, health, social and other refugee and migrant experiences relating to translated information. Our review found a small evidence base featuring studies with strong evaluation demonstrating effective forms of ‘language support’ for refugees and migrants from culturally and linguistically diverse backgrounds in Australia in a broad sense. However, there is a major gap in knowledge that is contributing to barriers in the use of online government information in Australia. In particular, there is an absence of evidence demonstrating what is effective in the use of machine translation with artificial intelligence, websites and other kinds of information technology for translating government information with refugees and migrants from culturally and linguistically diverse backgrounds. The oversight risks further excluding already marginalised groups from services and support. This paper makes a number of suggestions practitioners can take to address the issue and guidelines for future research.

show abstract

“…14 Many studies showed that the patient's treatment delay was related mainly with sociodemographic factors, socioeconomic status (SES), clinical variables, and psychological factors. [15][16][17][18] However, few studies looked into the effect of migration on treatment delay (the delay between being told to be hospitalized/receive a major treatment and a patient's hospitalization/getting a major treatment done). This study aims to investigate the relationship between rural-to-urban migration and treatment delay after the integration of urban and rural health insurance schemes in China.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Migration Duration on Treatment Delay Among Rural-to-Urban Migrants After the Integration of Urban and Rural Health Insurance in China: A Cross-Sectional Study

Niu

Liu

Wang

et al. 2020

INQUIRY

View full text Add to dashboard Cite

Few researches have been focused on the treatment delay of rural-to-urban migrants in China. Our study aimed to investigate the effect of migration duration on treatment delay among rural-to-urban migrants in tertiary hospitals. A cross-sectional study was conducted based on a sample of 727 patients and surveyed factors including sociodemographics, medical costs, migration, treatment delay, and health cost-coping strategies. Totally, 727 patients were included, of which 61 delayed their treatment and 666 had no treatment delay. Statistically significant differences were found between different migration duration groups in marital status, education, insurance, family annual income, residency, payment before treatment, reported disease, and migration duration ( P < .05). The results from multiple logistic regression showed that migration between 1 and 5 years (adjusted odds ratio [OR] = 7.24; 95% confidence interval [CI] = 1.59-32.87; P < .05) was considered the significant contributing risk factor for treatment delay after adjusting for age, sex, and other variables. To cope with their health expenditure, patients with treatment delay tended to use less savings and borrow more money than those without. Rural-to-urban migrants with 1 to 5 years of migration were the most vulnerable group of having treatment delay. Migrants were more likely to borrow money to cope with the health expenditure. Targeted services should be provided to meet different needs of migrants according to migration duration.

show abstract

The association between ethnicity and delay in seeking medical care for chest pain

Cited by 20 publications

References 72 publications

Ethnicity and outcomes in patients hospitalised with COVID-19 infection in East London: an observational cohort study

Ethnicity and outcomes in patients hospitalised with COVID-19 infection in East London: an observational cohort study

Do multilingual androids dream of a better life in Australia? Effectiveness of information technology for government translation to support refugees and migrants in Australia

The Effect of Migration Duration on Treatment Delay Among Rural-to-Urban Migrants After the Integration of Urban and Rural Health Insurance in China: A Cross-Sectional Study

Contact Info

Product

Resources

About