The UK Health Security Agency (UKHSA) has launched a national coding taxonomy specifically for incident learning in clinical imaging, MRI and nuclear medicine. This system is designed to enhance patient safety by providing a structured way to report, analyse, and learn from incidents, including both notifiable and non-notifiable events as well as near misses.

Prior to this initiative, there was no national system dedicated to analysing and learning from incidents in clinical imaging, MRI and nuclear medicine. The Clinical Imaging Board (CIB) recognised the need for such a system and tasked the Medical Exposures Group (MEG) at UKHSA with co-ordinating a multidisciplinary working party of modality specialists from across the four nations to take on this work.

Working with the modality specialists and professional bodies, a nationally agreed coding taxonomy was created to reflect the particular types of incidents that occur in clinical imaging, MRI and nuclear medicine including both equipment and procedural incidents. The taxonomy coding and incident learning system represents a significant step forward in enhancing patient safety and fostering a positive safety culture. This refined system focuses on the context or contributory factors that affect or influence incidents rather than assigning blame to individuals. It includes both notifiable and non-notifiable incidents as well as near misses, offering a comprehensive view of potential hazards and learning opportunities.

The coding offers a streamlined approach for the analysis of incidents and near misses across the modalities. It will allow staff to identify trends and provide opportunity for learning which in turn will help mitigate the risk of the incidents reoccurring. We hope to see this system support clinical staff in reporting incidents and near misses in a standardised way and strengthen reporting cultures within clinical departments.

At a national level this system will allow departments to benchmark their local analysis against the national picture. It is hoped this will assist with identifying emerging issues that perhaps may not be easily identified at a local level. In terms of patient safety, the analysis of the data will help direct future learning and inform local processes, procedures and risk assessments so these events may be mitigated.

The "User guidance and national coding taxonomy for incident learning in clinical imaging, magnetic resonance imaging and nuclear medicine" has now been published:

• National coding taxonomy for incident learning in clinical imaging, MRI and nuclear medicine


• User guidance and application of the national taxonomy for incident learning in clinical imaging, MRI and nuclear medicine

To aid in the practical implementation of the coding system, the user guide includes examples and scenarios for each pathway and contributory factor code.