Safe People
Lead applicant organisation name	University of Birmingham

Safe Projects
Project title	Understanding follow-up of incidental pulmonary nodules at UHB
Lay summary	Lung cancer is common and is most frequently diagnosed at stage III or beyond, meaning patients have a 10 percent chance of surviving for 10 years. One means for catching it early is lung cancer screening, which is currently being rolled out in certain places in the UK. However, another way is to follow up nodules that are found in the lungs when patients have scans of the chest area for other reasons, such as when scanning the heart. Patients with these nodules are supposed to be followed up according to clinical guidelines. However, there is evidence that patients are often lost at various stages along their care journey for multiple reasons. This may be leading to unnecessary harm to these patients. We want to look at reports from radiologists based on these scans and reports of how these patients have been followed up to understand the size of this problem by first using data from University Hospitals Birmingham. Our first step is to develop our natural language processing algorithm for identifying patients based on these CT scan reports.
Public benefit statement	"Access to these data will enable us to develop an algorithm for identifying patients who have been diagnosed with pulmonary nodules. This algorithm will then enable us to understand the extent of loss of patients to follow-up at UHB. Once developed, it would be possible to use the algorithm to classify CT scan reports in other NHS Trusts in the future as well. Together with additional qualitative research we are pursuing in parallel to understand how and why loss to follow-up may occur, this will enable design of interventions such as clinical decision making support tools to improve patient follow-up and help to identify lung cancer at a more survivable stage. The algorithm itself that we develop may also form a foundation of a future clinical tool that will be able to automatically generate clinical recommendations based on the nodule characteristics identified from free text CT scan reports, improving and partially automating patient follow-up."
Latest approval date	07/04/2025

Safe Data
Dataset(s) name	PATHWAY Research Data Hub: PWY016 dataset

Safe Setting
Access type	Data Licence Agreement between the collaborating organisations using secure and controlled data analysis environments.

Safe Outputs
Link	Not yet Published