Deriving and validating a clinical prediction rule for the diagnosis of asthma in primary care

Asthma is common in the UK. Accurate diagnosis is essential for good asthma management. Yet uncertainty about the best way to diagnose asthma can lead to missed diagnoses and under-treatment, or over-diagnosis leading to unnecessary treatmen. <p>Asthma is common in the UK, causing considerable illness, healthcare usage, and public expense. Accurate diagnosis is essential for good asthma management. Yet, uncertainty about the best way to diagnose asthma can lead to missed diagnoses and under-treatment, or over-diagnosis leading to unnecessary treatment and healthcare costs. To make it easier for doctors and nurses to identify and interpret important information gathered from patient suspected of having asthma, existing research database 'Avon Longitudinal Study of Parents and Children' (ALSPAC) will be used to identify feautres which predict who has asthma. This data contains information on a wide-range of socioeconomic, lifestyle, clinical, anthropometric and biological data on all family members repeatedly. The rule will be tested on anonymous routine data from UK GP's 'Optimum Patient Care Research Database'.</p> <p>ALPSAC: http://www.bristol.ac.uk/alspac OPCRD: https://opcrd.co.uk/</p>

Webpage:
https://www.healthdatagateway.org/dataset/842e8c5c-a298-4942-9ac4-f95d1a5f87b3

Licence:
Name: HDR UK Innovation Gateway Access
URL: https://www.hdruk.ac.uk/infrastructure/gateway/terms-and-conditions/

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alspac oprcd asthma diagnosis primary care prediction model

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