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Information: Convert data into actionable knowledge

How we use data to manage for quality is the cornerstone of a Quality Management System (QMS) and everyone has a role to play. We must ensure information is available and shared appropriately for all who need it.

Scope your data

Understand what data is currently collected and whether it adds value. Be clear on what data you would ideally have. If you are setting up a new service – build in a set of measures that will tell you if you are achieving your targets.

Select measures that will really allow you to understand the performance of your system

Where possible, co-develop the measurement approach with staff and patients. Apply the principles of measurement for improvement - separating measures into outcome, process and, where needed, balancing measures.

Triangulate quantitative, qualitative, performance, experience and outcome measures to understand the quality of services, efficacy of improvement work and impact of decisions made. Maintain the golden thread ensuring alignment between the measures across the organisation.

Visualise data to drive action and improvement

Track and present data over time. Use Statistical Process Control (SPC) charts and get used to talking about special cause and common cause variation. Be consistent with data presentation and be comfortable to challenge data that is requested in a way which does not support safe decision making e.g. aggregated data or Red, Amber, Green (RAG) ratings. Use established icons and markings to make interpretation easy for decision makers.

Ensure accessibility

Make sure the right people, have access to the right data, at the right time and are using it for the right reasons:

  • Make good strategic decisions
  • Guide improvement initiatives (improvement science)
  • Drive implementation programmes (implementation science)
  • encourage using ‘data for learning’ not judgement. Use your data to inform priority areas for focused improvements.

Focus on the fundamentals of good data practice but be open to innovation

Some of the developments in Artificial Intelligence (AI) have the potential to support organisations to convert data into actionable knowledge. This includes tools to understand population needs, monitor quality in real time and visualise measurement for improvement.

Supporting resources