Room: AAPM ePoster Library
Purpose: Checklists are an established method to reduce errors and are recommended by the AAPM MPPG 11.a and TG-275 as a strategy for physics plan review. However, their use is not widespread, standardized or effectively implemented. Our institution has leveraged existing functionality within our oncology information system (OIS) to implement a free and easily-implemented intelligent dynamic checklist (IDC) which links to the patient’s electronic medical record (EMR) to retrieve real-time contextual information for use when completing the checklist. This work demonstrates the reduction in errors achievable when using IDCs.
Methods: Standardized IDCs for treatment planning and physics plan review were designed and implemented in the Aria/Eclipse OIS (Varian Medical Systems, Palo Alto, CA). Using the patient’s EMR and planning data, the IDC compares prescription against plan, retrieving relevant tasks, appointments, documents and alerts as required for review. The physics plan review IDC was used to evaluate a total of 276 plans. An equal number of plans created while using the planning IDC were then checked. For each review, the number and type of QC issues (e.g. Prescription, Plan Quality, Documentation, Setup, etc.) were tabulated.
Results: Prior to the introduction of the treatment planning IDC, the rate of QC issues detected during physics plan review was 23.2%. After introducing the IDC, the rate of QC issues decreased to 6.0%. Of these ongoing issues, 58% were of a nature not covered by the treatment planning IDC. The distribution of QC categories changed after introducing the IDC, with less issues related to documentation, naming, prescription, QA and setup, and more issues related to treatment plan quality.
Conclusion: The use of IDCs reduced the rate of QC issues occurring during treatment planning and shifted the distribution of QC issues towards complex plan quality issues that precluded easy detection and correction via a checklist.
Quality Control, Quality Assurance, Computer Software
IM/TH- Formal Quality Management Tools: Error taxonomies and incident reporting analyses