You must propose a solution to one of the 3 challenges in each application. If you want to apply for more than one challenge, you will need to submit a separate application for each challenge.
Additional information on the clinical background to the challenges will be available when you register for the competition.
Challenge A: diabetic foot ulceration
Your project must develop an automated mechanism that assesses the risk of diabetic foot ulceration. The mechanism must:
- use recognised risk factors
- be suitable for use at the point of care (POC)
- work with new or existing datasets
- create algorithms using artificial intelligence or machine learning, or a combination of both
The new algorithms must:
- use data extraction and integration to address individual risk stratification for foot ulceration and amputation
- tackle risk factor management for cardiovascular morbidity and mortality
The technology must provide feedback reports and alerts of foot and mortality risk. These can be through audio-visual, haptic or bio-feedback, as critical components and active ingredients in effective behaviour change interventions.
The technology can include software applications, data-exchange integration platforms and innovative technology including novel POC approaches. These must aid clinical and patient-facing models for personalised risk stratification, monitoring, targeted interventions or treatment decision support.
Solutions may also consider expansion of POC applications that capture and integrate other processes of care through assessment of additional diabetes risk. This can include factor screening for blood pressure, urine micro albumin measurement and retinal imaging.
Your project must also have:
- the ability to be effectively and securely integrated to NHS Scotland IT infrastructure
- an understanding of how any technology solutions or products will be economically sound and affordable for the NHS if adopted
Challenge B: diabetes care pathway for inpatients
Your project must develop a decision support tool and alert mechanism for clinical staff. This must improve the care of patients admitted to hospital, with a pre-existing diagnosis of diabetes. The tool must use available inpatient data sources to:
- improve triage
- prevent medication errors
- identify emergencies
- streamline the diabetes care pathway
By improving the clinical care of inpatients with a pre-existing diagnosis of diabetes, the support tool will deliver safer and better care on admission to hospital. This would include:
- managing and reporting hypoglycaemia (low blood sugar)
- guided insulin prescribing
- improved management of blood glucose
In phase 1 you will focus on a 3-month exploratory project with clinicians with the aim to get a deep understanding of clinical pathways and the most pressing needs.
To improve the identification (case finding) of people at risk of osteoporosis and fracture, including those with diabetes your project must:
- develop improved, less manual mechanisms of identifying patients with fractures who should be followed up by the Fracture Liaison Service (FLS). This may extend to automation of existing processes which largely rely on radiology reports from X-ray imaging. Images will be available if required.
- develop a more tailored solution to FLS identification for patients with diabetes that may require access to detailed clinical data collected over a period of time, such as glucose control and adherence to therapy.
Data sources available for this challenge include unstructured radiology reports, emergency department attendance reports (ED Trak), national diabetes dataset (SCI diabetes), bone metabolism data, and a historic dataset of patients identified to be at risk.