Thursday 11 April 2024 | 15:00-16:00

Format: Workshop

Stream: Science

Content filters: n/a

Pierre Barker Institute of Healthcare Improvement, USA (Chair)

PART 1: Data-driven quality and safety improvement for primary healthcare in Anhui, China

By late 2019, an artificial intelligence assistance (AIA) for primary healthcare had been introduced throughout Anhui, an inland province with 6.1 million people located in east China. This session introduces how this province-wide AIA is functioning, what changes it has brought into the real-world primary healthcare, what challenges it is still facing and what opportunities it holds for future quality and safety improvement.

As a result of this session, participants will be able to:

• Know the state of art of AI applications in primary healthcare in Anhui and China


• Derive lessons from a real-world case-study, on
  
  
  
  • procedures, drivers and  barriers in disseminating the AIA
  
  
  • major benefits and risks from the AIA
  
  
  • pragmatic framework, perspectives and methods for implementing and evaluating the AIA
  
  
  
  

Debin Wang Anhui Medical University, China

 

PART 2: Can developmental evaluation realise the promise of AI in improving patient experience?

Developing, implementing and sustaining new technology and quality improvement within our health and care services is notoriously difficult. The value of patient experience to drive improvement is well recognised. So too, is the mobilisation of frontline staff in using data to drive improvement.
Imperial College London have developed their natural language processing model to optimise NHS staff engagement with, and use of, Friends and Family Test data to identify and act upon patient-led improvement priorities.
AQuA have adopted developmental evaluation principles and methodology to underpin a learning system across traditional boundaries that facilitates stakeholder involvement in capture and review of emergent data to understand progress, inform activity, and deliver future sustainability.

As a result of this session, participants will be able to:

• Understand the aims of Imperial College’s natural language processing model to visualise NHS patient experience data to engage and support frontline staff in visualising data to drive improvement


• Build awareness of developmental evaluation principles and flexible design


• Explore the potential role of developmental evaluation in rapid development and implementation of complex technical and quality improvement initiatives

Ruth Yates Advancing Quality Alliance (AQuA), England