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Asthma Diagnosis in Primary Care: A Clinical Prediction Model – Luke Daines

Nearing completion of his studies as PhD student, Luke Daines’ blog series reflects on a workshop he held in June 2020 focussing on asthma diagnosis in primary care

Every year in the UK there are approximately 6 million general practice consultations for asthma and 100,000 hospital admissions contributing to an estimated annual cost to the NHS of £1.1billion for the provision of asthma care in the UK. Making an accurate diagnosis of asthma, is important to ensure that patients get the right care at the right time.

However, making a diagnosis of asthma can be difficult. Guidelines for asthma provide different recommendations for health professionals, leading to uncertainty about how best to achieve a diagnosis. The availability of diagnostic tests is variable, with Fractional exhaled Nitric Oxide (FeNO) testing still poorly accessible by UK primary care practices. Evidence of mis-diagnosis in the community estimate up to a third of those previously diagnosed with asthma may not have current disease. Mis-diagnosis of asthma can lead to individuals not receiving the treatment they need, ongoing symptoms and reduced quality of life, coupled with unnecessary costs (for instance inappropriate prescribing) for healthcare services.

Clinical prediction model for asthma diagnosis in primary care

My PhD, funded by the Chief Scientist Office, Scotland, has focussed on creating and testing a clinical prediction model designed to support doctors and nurses in primary care identify the probability that their patient has asthma. The model was developed using a dataset of nearly 12000 children and young people from the Avon Longitudinal Study of Parents and Children (ALSPAC). The model is a mathematical equation that can calculate the probability that a child/young person has asthma.

To be useable by health professionals, it needs to be incorporated into a software. I was fortunate to receive additional funding from Asthma UK/Innovate UK to develop the prediction model into a software. The result is a clinical decision support system (CDSS) which we have called Asthma Diagnosis Decision Aid (ADxDA). As I near the end of my PhD, I was keen to share my findings and to gain feedback from a broad range of stakeholders, I was delighted to do so during a workshop on the 10th June 2020.

Workshop with multiple stakeholders

Due to the Covid-19 situation, the workshop was held virtually bringing both opportunities and challenges! The biggest advantage was the opportunity to include stakeholders from further afield, including a Professor of primary care respiratory medicine from the Netherlands, and a parent of a child with asthma from the south of England who would otherwise been unable to attend. It was great to have feedback from people from many different backgrounds including GPs, patient representatives, nurse practitioners, researchers, statisticians, paediatricians, physicians, Scottish government, Asthma UK British Lung Foundation partnership and Tactuum (digital healthcare services).

The workshop has informed the next steps that I will take after I complete my PhD studies. I’ve learned what the priorities are for both patients and professionals, and the implications that need to be considered when implementing a decision support system in practice.

Find out more about the ADxDA Project

See Luke Daines' student profile page