Enhancing feedback from incident reporting: Translating information into action
Start and end dates
September 2013-September 2016
Internationally, healthcare organisations have struggled with the question of how to monitor variations in patient safety and how to implement early warning and surveillance systems that support learning and increase the resilience of the system to prevent future patient safety incidents. One such approach to gathering intelligence on variations in safety is incident reporting. Many health systems now have national or centralised incident reporting systems (CIRS) where incidents can be analysed for trends and signals capable of contributing useful learning from failures and variations in care.
In the UK, the National Patient Safety Agency (NPSA) and National Reporting & Learning System (NRLS) was established based upon proven models developed in transportation and high risk industries. In such systems, analysis of reports from front line staff led to dissemination of feedback from a centralised system to organisations and reporters, with modes of feedback having been developed to accommodate the spectrum of incident types within the NHS.
In 2009, a systematic review by Benn et al sought to review available literature on feedback from local incident reporting strategies. Combined with data collected from interviews with experts in high risk domains, a Safety Action and Information Feedback from Incident Reporting Framework (SAIFIR) was developed, defining the key modes of feedback needed for effective action and learning. The review highlights the need for timely action and feedback to improve systems and raise awareness of vulnerabilities within an organisation and prompts the need for further work to evaluate different methods of translating information to action and feedback.
This PhD project seeks to address the gap in current knowledge concerning the best way to translate information on patient safety incidents into meaningful action for NHS organisations and to develop methods for closing the safety-action-feedback loop in healthcare systems.