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Leveraging a Communication Tool to Assess IMRT Planning Process Efficiency and Identify Improvement Opportunities


J Evans

J Evans*, Virginia Commonwealth University, Richmond, VA

Presentations

SU-F-P-12 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall


Purpose: To utilize an existing patient-specific IMRT QA communication tool to quantify our department’s compliance with existing IMRT planning policies and to identify opportunities for improvement.

Methods: A centralized network-based spreadsheet is utilized by our dosimetrists to communicate to the physics team when an IMRT plan is ready for patient-specific QA measurement. Since Feb. 2014, the dosimetrists and physicists track additional date information for each case including treatment start, contour approval, plan approval, and QA measurement. Since Jan. 2015, our team also tracks if, and why, a patient plan requires more than one QA measurement. Two time periods were analyzed: Feb. 2014 to Dec. 2014 and Jan. 2015 to Dec. 2015. The Excel “networkdays” function was used to calculate the number of days between process steps for each case. Histogram analysis was used to quantify environmental hazards created by compressed timelines for QA. The rate of and the reasons for QA re-measurement was also quantified.

Results: In 2014, 27.3% of QA measurements were performed the day before treatment start. From this, we modified our QA policies and staffing. In 2015, this day before start QA rate was reduced to 20%, but is ultimately limited by physician plan approval. In 2014, 29% of cases were approved by the physician within 2 or fewer days of treatment start. In 2015, this rate increased to 38% of cases. In 2015, 16.4% of QA measurements were a re-measurement. The 2 most common themes for a re-measurement were clinical reasons (re-sim, re-plan, contours modified) or a measurement setup error, e.g. the MatrixX ion chamber plane being left in a high dose gradient region.

Conclusion: Leveraging an existing communication tool has allowed us to quantify our IMRT process performance, identify bottlenecks for improvement, and quantify improvement following policy changes.



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