Open AccessDevelopment and implementation of a radiation therapy incident learning system compatible with local workflow and a national taxonomy
Author(s) -
Montgomery Logan,
Fava Palma,
Freeman Carolyn R.,
Hijal Tarek,
Maietta Ciro,
Parker William,
Kildea John
Publication year - 2018
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.12218
Subject(s) - workflow , incident report , computer science , software , radiation oncology , medical physics , process management , radiation therapy , medical education , medicine , engineering , database , operating system , computer security
Purpose Collaborative incident learning initiatives in radiation therapy promise to improve and standardize the quality of care provided by participating institutions. However, the software interfaces provided with such initiatives must accommodate all participants and thus are not optimized for the workflows of individual radiation therapy centers. This article describes the development and implementation of a radiation therapy incident learning system that is optimized for a clinical workflow and uses the taxonomy of the Canadian National System for Incident Reporting – Radiation Treatment ( NSIR ‐ RT ). Methods The described incident learning system is a novel version of an open‐source software called the Safety and Incident Learning System (Sa ILS ). A needs assessment was conducted prior to development to ensure Sa ILS (a) was intuitive and efficient (b) met changing staff needs and (c) accommodated revisions to NSIR ‐ RT . The core functionality of Sa ILS includes incident reporting, investigations, tracking, and data visualization. Postlaunch modifications of Sa ILS were informed by discussion and a survey of radiation therapy staff. Results There were 240 incidents detected and reported using Sa ILS in 2016 and the number of incidents per month tended to increase throughout the year. An increase in incident reporting occurred after switching to fully online incident reporting from an initial hybrid paper‐electronic system. Incident templating functionality and a connection with our center's oncology information system were incorporated into the investigation interface to minimize repetitive data entry. A taskable actions feature was also incorporated to document outcomes of incident reports and has since been utilized for 36% of reported incidents. Conclusions Use of Sa ILS and the NSIR ‐ RT taxonomy has improved the structure of, and staff engagement with, incident learning in our center. Software and workflow modifications informed by staff feedback improved the utility of Sa ILS and yielded an efficient and transparent solution to categorize incidents with the NSIR ‐ RT taxonomy.