Digital health

The Bedside Clinical Guidelines app

In collaboration with Clinicians at the University Hospital North Midlands, we have been investigating and developing efficient methods for presenting and authoring pre-existing book-based clinical guidelines, called the 'Bedside Clinical Guidelines (BCGs)', for use on mobile devices. The BCGs have supported care at the bedside since 1996 and are currently utilised across 14 NHS Trusts throughout the UK, and aim to provide “consistent, evidence-based management of patients in acute hospital settings" for 'in the moment' bedside use. Over the past 5 years we have followed a user-centred design (UCD) approach using a combination of methods such as observation in the hospital, focus groups, think aloud, card sorts and questionnaires.

We have now produced a functional clinical guidelines app that we hope to launch into various trusts over the next few years. We then plan to research how clinicians actually use mobile apps like this for their work (beyond standard surveys) and how the usage data from these apps can be analysed to determine patterns of use and improve how information is presented to different types of users.

Feedback from clinicians

"This will be a really useful tool" ... "This would be handy on the wards" ... "I prefer it to the actual guidelines" ... "It will save a lot of time" ... "Less likely to make mistakes"

BCG app screenshots 500 px width

Above: Screenshots of the BCG app

Key papers

Health technologies, wearables and sensing systems

Health technologies, wearables and sensing systems offer opportunities for improved patient monitoring and individual self-management of health and wellbeing. We research, design, evaluate and prototype digital health technologies, wearables and sensing systems and collaborate with clinicians, health researchers, engineers and enterprise partners.

Our research encompasses Internet of Things (IoT) devices including wearables, sensing systems and Internet of Medical Things (IoMT) devices such as epilepsy seizure monitors and activity trackers. Our projects innovate system designs and contribute insights into the accuracy, usability, performance, sustainability and lifecycles of devices and systems. We also create novel datasets and enable new insights using AI, data mining and machine learning algorithms.

Our projects include:

  • Analyses of federated learning and Internet of Medical Things (IoMT) data for patient care
  • Assessments of wearable health technologies including evaluations of wearable heart rate accuracy and analyses of device updates
  • Evaluations of epilepsy seizure monitors
  • Prototyping of wearable systems and smart injection systems with clinical collaborators and health researchers