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Category: Publications

Publication: Prevalence and predictors of annual asthma reviews in Scottish primary care data

Is it too late to say Happy New Year?  I haven’t posted any updates in a while – very sorry!

New(ish) paper – Prevalence and predictors of annual asthma reviews in Scottish primary care data

Our study aimed to investigate the incidence and factors associated with attendance of annual asthma reviews, using electronic health records for approximately 50 000 Scottish asthma patients, between 2008 and 2016.

There was a median of 381 days between subsequent reviews. Reviews in the index year were strongly associated with reviews in the following year (odds ratio 1.76 [1.68-1.84]). In contrast, asthma consultations (excluding reviews) in the index year were associated with a lower odds of having a review in the following year (0.48 [0.46-0.51]). Those aged 18-35 in the index year, or with missing address in the practice registration data, were the least likely age group to have an asthma review in the following year.

Reviewing the delivery of asthma care identifies patients who may be slipping through the gaps by receiving only reactive asthma care rather than the structured, preventative care which can be delivered through annual reviews. Understanding the risk factors for not receiving an annual review can be leveraged to create more effective review invitations, such as explaining the specific content of reviews, introducing new contact methods to improve health equity, and reviewing the algorithm used to determine who is invited.

Publication: Cause of death coding in asthma

We’ve recently published a paper in BMC Medical Research Methodology on how cause of death is ICD10 coded in people with asthma.  This was a collaboration between myself, Dr. Alexandria Chung (an NHS Lothian Clinical Research Fellow), and George Addo Opoku-Pare, who I was lucky enough to be paired with for the HDRUK Black Internship Program last year.  You can read more about that here, and read about George’s experience here.

Our study investigated 91,022 deaths recorded in a Scottish longitudinal linked electronic health record dataset between 2000 and 2017. Asthma-related deaths were identified by the presence of any of ICD-10 codes J45 or J46, in any position. These codes were categorized either as relating to asthma attacks specifically (status asthmatic; J46) or generally to asthma diagnosis (J45).

We found that less than 1% of asthma-related mortality records used both J45 and J46 ICD-10 codes as causes. Infection (predominantly pneumonia) was more commonly reported as a contributing cause of death when J45 was the primary coded cause, compared to J46, which specifically denotes asthma attacks.

Further inspection of patient history can be essential to validate deaths recorded as caused by asthma, and to identify potentially mis-recorded non-asthma deaths, particularly in those with complex comorbidities.

Derivation and validation of an asthma diagnosis prediction model for children and young people in primary care

Dr. Luke Daines (Edinburgh University) has recently published in Wellcome Open Research on an asthma diagnosis prediction model for children and young people in primary care.  The logistic regression based prediction model was derived using the Avon Longitudinal Study of Parents and Children (ALSPAC) data linked to electronic health records, and validated in the Optimum Patient Care Research Database (OPCRD).   Predictors included in the final model were wheeze, cough, breathlessness, hay-fever, eczema, food allergy, social class, maternal asthma, childhood exposure to cigarette smoke, prescription of a short acting beta agonist and the past recording of lung function/reversibility testing. In the external validation dataset the C-statistic was 0.85, 95% CI 0.83–0.88.  Following further evaluation of clinical effectiveness, the prediction model could be implemented as a decision support software.

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