Bookmarks
ID 372: External validation and update of an asthma exacerbation risk prediction model for adults
Safe People
Organisation name
Imperial College London (ICL)
Applicant name(s)
Funders/ Sponsors
Safe Projects
Project ID
ID 372
Lay summary
We would like to use Whole Systems Integrated Care (WSIC) data to externally validate our prediction model. We will try different types of ML models that might perform better than logistic regression.
Public benefit statement
A prediction model will be available for clinicians to identify patients at risk of future asthma attacks. Clinical outcomes for these patients will improve as their future asthma treatment and management to prevent future asthma attacks using combined evidence from their medical records. Outputs from our study will help to determine characteristics of people with asthma who are more likely to have worse outcomes. This is turn can lead to further risk prediction models that can help predict which people are more likely to develop asthma or have an asthma attack or die in people who already have asthma. Outputs from this study could also lead to interventional studies to improve early asthma detection and better management of specific groups of patients with asthma. Ultimately, a better model will lead to better decision making and a validated model will give HCPs the confidence that it will work in practice.
Other approval committees
Latest approval date
19/10/2023
Safe Data
Dataset(s) name
Safe Setting
Access type
TRE