RE-BLEED: A Digital Platform for Identifying Bleeding Patients - a Feasibility Study

Bleeding affects up to 40% of all trauma patients, up to 30% of all surgery patients and is one of the commonest causes of death for women giving birth. The presentation and features of bleeding are different between patients - in some cases bleeding is very obvious to recognise, but in other cases bleeding is more "hidden", for example in the stomach. Bleeding must be stopped promptly to prevent severe illness or death.

Many studies have shown differences in how patients who bleed are treated. There is also variation in how individual patients respond to the same treatment, with some patients doing better than others. Understanding how variation in practice and patient characteristics affect outcomes will help researchers and clinicians design and test improvements in care.

Patients in hospital have regular tests that measure levels of the different types of cells in their blood and its ability to clot. For example, a drop in red blood cells can indicate that patients have suffered bleeding. More advanced blood tests are available that can provide more detailed information on why patients are bleeding and what treatments might be most effective.

This study aims to develop a real-time, hospital-wide digital system to identify patients in hospital who have suffered from bleeding and test whether this system could be used in the future to potentially identify patients to recruit into trials of new treatments or blood tests.

To do this, the investigators will:

• Assemble a panel of experts to identify criteria (for example, specific blood test results and drug prescriptions) that could indicate a patient has suffered from bleeding
• Use historical electronic patient records to test how well these criteria identify patients who have received treatments for bleeding (blood transfusion)
• Develop and refine a web-based digital system where the most useful criteria can be applied in "real-time" to identify bleeding patients
• Test how well the digital platform identifies bleeding patients
• Test whether a significant number of patients identified by the digital platform are willing to allow their routine blood samples tested for blood clotting and endothelial factors.

Inclusion criteria

Retrospective cohort:

• Adults aged between 16 and 110
• Admitted to hospital (Oxford University Hospitals NHS Foundation Trust) or attended the emergency department between 1/3/2011 to 31/8/2023

Prospective cohort:

• Adults aged between 16 and 110
• Admitted to hospital (Oxford University Hospitals NHS Foundation Trust) or attended the emergency department between 1/10/2021 to 31/8/2023

Exclusion criteria

Both retrospective and prospective cohorts:

• Patients who inform us directly that they do not wish their records used in this research study
• Patients who have completed the NHS Opt-out.