Case Study: Optimizing NSIR-RT for the clinic
Under the guidance of CPQR Steering Committee member and McGill faculty member, John Kildea, medical physics Masters student Logan Montgomery undertook a thesis project titled: An evaluation of incident learning using the taxonomy of the National System for Incident Reporting – Radiation Treatment. The goals of this project were to create an incident learning system compatible with NSIR-RT and optimized for clinical workflow, and to evaluate the NSIR-RT taxonomy using real incident data classified by staff at the McGill University Health Centre. CPQR sat down with Logan to see how this project helped McGill, and may help your centre too!
Q: Like many radiation treatment programs in Canada, McGill already had a local incident reporting system, can you tell us what you hoped to accomplish?
A: Learning from incidents at the institutional-level plays an important role in local quality improvement. The logical next step is to share data and lessons learned at a national level, and learn from the experiences of others. To this end, we adopted an open-source software called The Safety and Incident Learning System (SaILS) that was developed at the Ottawa Hospital Cancer Centre, and modified it for compatibility with NSIR-RT. In addition to aligning our taxonomy with that of NSIR-RT, this project also focused on improving staff engagement and optimizing workflow.
Q: And what did you learn during this process?
A: Owing to the robustness of the SaILS framework, it was straightforward to integrate the NSIR-RT taxonomy into SaILS. After an initial development period, we launched SaILS in our centre in January 2016. Our unique approach has allowed staff in our centre to report and investigate incidents using the NSIR-RT taxonomy directly. We collected feedback from staff and reviewed incident data submitted to SaILS to evaluate the clarity and completeness of the NSIR-RT taxonomy. These findings were relayed to CIHI and CPQR to aid in revising NSIR-RT to better meet the needs of the Canadian radiation therapy community.
Q: I understand that you’ve also added some extra functionality to SaILS as well, can you describe that?
A: Staff engagement is crucial to the success of incident learning. Thus, we incorporated incident tracking functionality into SaILS that allows staff to follow-up on incidents they reported and review associated outcomes (which are assigned and documented by other users during incident investigations). This facilitates transparency in the incident learning process, documents the impact of each incident report, and encourages staff to continue reporting incidents.
An intuitive data visualization toolkit was included in SaILS that allows all staff to plot aggregate incident data and examine trends therein. Additionally, we added two features that leverage existing data to minimize the amount of time required to classify incidents. The first of these utilizes existing patient and treatment information in our electronic medical record to automatically populate information in incident reports and provide users with relevant documentation. The second is an incident templating feature, which allows users to create templates for specific types of incidents and apply them to similar incidents in the future.
Other notable functionality within SaILS includes compatibility with incident/accident reporting policies in Quebec, a robust incident search feature, and user-specific dashboards.
Q: How can your experiences be useful for other centres across the country?
A: Transparency, sharing, and open-source software are at the heart of collaborative incident learning. Thus, our revised version of SaILS is also provided as open-source software and is available for download at: https://bitbucket.org/mcgillmedphys/sails_nsir. While the nuances of incident reporting differ from one centre to the next, there is substantial commonality between them. Given the flexibility of SaILS we are confident the software could prove useful to other Canadian centres who try it.
Our experience with the NSIR-RT has been a positive one, and the taxonomy has provided improved structure to incident learning in our radiation therapy centre. The efficacy of the NSIR-RT initiative, and thus the safety of Canadian radiation therapy patients, will only improve as more centres become involved. We thus encourage everyone to get on board, either with NSIR-RT directly or with SaILS!
If you are interested in this work you can view a poster recently presented by Dr. Kildea and Mr. Montgomery at the CPAC Conference 2017.