Ethnic differences in healthcare utilisation and diagnosis after first presentation with breathlessness: a...

There are known delays to diagnosis for chronic respiratory disease and recognised health inequalities in outcomes. We therefore investigated the association between ethnicity and subsequent healthcare utilisation and receipt of an explanatory diagnosis after a first presentation with breathlessness. Clinical Practice Research Datalink (CPRD) GOLD data linked to Hospital Episode Statistics (HES) and death registries were used to identify adults with a first-recorded code for breathlessness (index-date). Ethnicity was determined using the Hemingway algorithm. Rates of primary care consultations, secondary care referrals and hospital admissions within six and 24 months after index-date were examined using negative binomial regression. Logistic regression was used to estimate odds of receiving an explanatory recorded diagnosis for breathlessness during these timeframes. Models were adjusted for age, sex, socioeconomic status and ≥ 2 pre-existing long-term conditions. Amongst 88,857 included patients, 3336 were of South Asian ethnicity and 1506 of Black ethnicity. Compared to patients of White ethnicity, South Asian patients had significantly increased rates of primary care consultations and unplanned hospital admissions within six and 24 months (24 months IRR 1.13 [1.10-1.16] and 1.34 [1.25-1.45] respectively). Conversely, patients of Black ethnicity had significantly lower rates of primary care consultations within 24 months (IRR 0.95 [0.92-0.99], but significantly increased rates of unplanned hospitalisations within six and 24 months (IRR 1.33 [1.19-1.50]). However, both groups had significantly lower odds of receiving an explanatory diagnosis for breathlessness. After a first presentation with breathlessness, we observed a higher rate of unplanned hospitalisations yet a lower rate of receiving an explanatory diagnosis in patients of non-white ethnicity. Understanding the reasons and implications of these differences is critical to reduce potential health inequalities.