A Practice-based Taxonomy for Radiation Treatment Errors

Authors: Catarina Lam, MBA, BScemail address, Gaylene Medlam, BSc, Anne Wighton, BSc, Stephen L. Breen, PhD, Jean-Pierre Bissonnette, PhD, Tom S. McGowan, MBA, MD, Marco Carlone, PhD, Micheal F. Milosevic,

An absence of a common language for incident classification limits knowledge sharing within and between organizations in the radiotherapy community. This challenge provided the motivation to develop a clinically relevant taxonomy for radiotherapy errors.

Materials and Methods

This was a multicenter, prospective study that consisted of three phases: (1) an initial version of the taxonomy was developed based on the World Health Organization Conceptual Framework for the International Classification for Patient Safety and taxonomy models from radiotherapy and other industries; (2) the taxonomy was evaluated using actual incident data from a single practitioner and revised; and (3) face validity testing of the taxonomy was performed by two additional practitioners from different radiotherapy centers using simulated incident cases.

The taxonomy consisted of seven classes: incident nature, impact, incident type, stage of origin, stage of discovery, contributing factors, and preventative strategies. Each class was divided into subcategories containing increasingly detailed information. A total of 191 consecutive incidents were classified in phase 2 to ensure no further revision to the taxonomy was required. In phase 3, low interobserver agreement (<60%) was obtained for most classes of the taxonomy in the first face validity test. After revisions were made to the taxonomy based on practitioners' feedback, a second face validity test yielded a high degree of agreement (70%–93%) for all classes.

Our multiphase, iterative approach has yielded a workable and multidimensional set of incident classifiers that can be scaled to accommodate local, regional and discipline-specific requirements. Opportunities exist to implement this taxonomy in institutional and national incident databases to facilitate incident learning within and between institutions.