Best practices study to enhance the quality of multi-disciplinary teams in lung cancer care.

Abstract

1532 Background: Regular meetings at multi-disciplinary teams (MDTs) constitute a key moment in the care pathway in lung cancer, where physicians collectively discuss patient cases and decide on treatment plans. MDTs arguably increase the volume of patients treated, improve diagnosis, and positively impact on survival. However, the way MDTs are organized and function is variable across hospitals, countries and continents. Variations in MDT processes may lead to sub-optimal outcomes, such as inconsistencies on the numbers of patients treated with curative intent as well as variable 5-years survival rates for lung cancer. The importance of MDTs is ever increasing, as the therapeutical landscape is getting more complex every year, and treatments are evolving from a one-size-fits-all to a personalized approach. Methods: In this study, we gather the best practices in MDT processes, capabilities and governance in 24 leading hospitals throughout Europe and Canada. We map the MDT practices of each hospital into a coherent framework, and identify KPIs and best practices by conducting semi-structured interviews with health care professionals in each hospital and performing workshops with the entire MDT team. The primary research focuses on five key categories: access to the MDT, processes, technology (such as EMR, data sharing tools, and artificial intelligence), culture and capabilities. Results: We see a high variation in the way MDTs are organized, in time for discussion per patient, in the model of care and current MDT practices across the 24 hospitals in this project, along our five identified categories. We developed an MDT maturity model where we score individual elements within these five categories to identify the hospitals with the best MDT practices, and a total of 23 key success factors along the MDT process. The maturity model and the key success factors can be used as a self-assessment tool for MDT-teams for continuous quality improvement. Conclusions: MDTs have the potential to be a standard part of the patient care pathway, where excellence is consistently achieved when discussing patient cases. This work has identified the practices that are done best in leading hospitals and that have the potential to be progressively adopted. Furthermore, we see that the potential of decision support tools and other artificial intelligence is rarely leveraged by MDTs.