Asthma prescribing, ethnicity and risk of hospital admission: an analysis of 35,864 linked primary and secondary care records in East London.
Sally A HullShauna McKibbenKate HomerStephanie Jc TaylorKatharine C PikeChris GriffithsPublished in: NPJ primary care respiratory medicine (2016)
Inappropriate prescribing in primary care was implicated in nearly half of asthma deaths reviewed in the UK's recent National Review of Asthma Deaths. Using anonymised EMIS-Web data for 139 ethnically diverse general practices (total population 942,511) extracted from the North and East London Commissioning Support Unit, which holds hospital Secondary Uses Services (SUS)-linked data, we examined the prevalence of over-prescribing of short-acting β2-agonist inhalers (SABA), under-prescribing of inhaled corticosteroid (ICS) inhalers and solo prescribing of long-acting β2-agonists (LABA) to assess the risk of hospitalisation for people with asthma for 1 year ending August 2015. In a total asthma population of 35,864, multivariate analyses in adults showed that the risk of admission increased with greater prescription of SABA inhalers above a baseline of 1-3 (4-12 SABA: odds ratio (OR) 1.71; 95% confidence interval (CI) 1.20-2.46, ⩾13 SABA: OR 3.22; 95% CI 2.04-5.07) with increasing British Thoracic Society step (Step 3: OR 2.90; 95% CI 1.79-4.69, Step 4/5: OR 9.42; 95% CI 5.27-16.84), and among Black (OR 2.30; 95% CI 1.64-3.23) and south Asian adult populations (OR 1.83; 95% CI 1.36-2.47). Results in children were similar, but risk of hospitalisation was not related to ethnic group. There is a progressive risk of hospital admission associated with the prescription of more than three SABA inhalers a year. Adults (but not children) from Black and South Asian groups are at an increased risk of admission. Further work is needed to target care for these at-risk groups.
Keyphrases
- primary care
- healthcare
- chronic obstructive pulmonary disease
- lung function
- adverse drug
- emergency department
- allergic rhinitis
- palliative care
- young adults
- general practice
- quality improvement
- electronic health record
- multiple sclerosis
- acute care
- mental health
- machine learning
- cross sectional
- pain management
- air pollution
- deep learning
- tertiary care