Developing Healthcare Team Observations for Patient Safety (HTOPS): senior medical students capture everyday clinical moments

Abstract

Abstract Background Aviation has used a real-time observation method to advance anonymised feedback to the front-line and improve safe practice. Using an experiential learning method, this pilot study aimed to develop an observation-based real-time learning tool for final-year medical students with potential wider use in clinical practice. Methods Using participatory action research, we collected data on medical students’ observations of real-time clinical practice. The observation data was analysed thematically and shared with a steering group of experts to agree a framework for recording observations. A sample of students (observers) and front-line clinical staff (observed) completed one-to-one interviews on their experiences. The interviews were analysed using thematic analysis. Results Thirty-seven medical students identified 917 issues in wards, theatres and clinics in an acute hospital trust. These issues were grouped into the themes of human influences, work environment and systems. Aviation approaches were adapted to develop an app capable of recording real-time positive and negative clinical incidents. Five students and eleven clinical staff were interviewed and shared their views on the value of a process that helped them learn and has the potential to advance the quality of practice. Concerns were shared about how the observational process is managed. Conclusion The study developed an app (Healthcare Team Observations for Patient Safety—HTOPS), for recording good and poor clinical individual and team behaviour in acute-care practice. The process advanced medical student learning about patient safety. The tool can identify the totality of patient safety practice and illuminate strength and weakness. HTOPS offers the opportunity for collective ownership of safety concerns without blame and has been positively received by all stakeholders. The next steps will further refine the app for use in all clinical areas for capturing light noise.