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About Us

The DynAIRx collaborative brings together patients, clinicians, carers, data and artificial intelligence (AI) experts together to address the major problem of medication burden.

Understanding the problem to develop a solution

DynAIRx will focus on three groups of people at high risk of rapidly worsening health from multimorbidity. These groups are:

  • Older people with frailty
  • People living with mental and physical health problems
  • Other people with four or more long-term health conditions taking ten or more medicines.

We know that multimorbidity increases with age. Currently, people with multimorbidity are treated separately for each condition and prescribed different medicines, each to treat one condition. Taking multiple medicines, or polypharmacy, increases the likelihood of serious side effects.

Integrating advanced technologies to solve modern problems

The team has a stated goal of developing AI that analyse and process data including medical records, hospital admission figures, and other adverse outcomes, to produce visual graphics representing a patient journey. These graphics will then be tested in GP surgeries across the region to understand their effectiveness via feedback from practitioners and patients.

Working in partnership, bringing together expertise from multiple sectors

DynAIRx will be led jointly by Professor Iain Buchan and Dr Lauren Walker and managed by the University of Liverpool in close collaboration with our key partners at the Universities of Leeds, Manchester and Glasgow.

It will be delivered by people across a wide range of allied organisations including Merseycare, Liverpool Health Partners, SPARK, and North West Coast Clinical Research Network.

We have created an animation to explain what the DynAIRx study is aiming to do

Dr Lauren Walker

Patients who are managing many different conditions find themselves navigating their way through numerous appointments for clinics, imaging, blood tests and so on. The information about their cares becomes scattered across numerous systems. It can become difficult to identify those who are most at risk, and hence need to be prioritised, among the different care settings. DynAIRx aims to bring that information together using artificial intelligence techniques that can create visual summaries of patient journeys to make it easier for prescribers to identify what needs to be done.

Dr Lauren Walker

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