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SU‐E‐T‐372: Quality Assurance Plan Veto (QAPV): Reincarnation of Record and Verify System and Its Potential Value
Author(s) -
Gutti V,
Noel C,
Yang D,
Bosch W,
Mutic S,
Ford E,
Terezakis S,
Santanam L
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4814806
Subject(s) - quality assurance , dicom , workflow , computer science , radiation treatment planning , reliability engineering , medical physics , medicine , database , radiation therapy , artificial intelligence , engineering , surgery , external quality assessment , pathology
Purpose: To quantify the potential impact of implementation of IHE‐RO Quality Assurance Plan Veto (QAPV) profile on patient safety of external beam radiation therapy operations. Methods: An institutional database of events (errors and near misses) was used to evaluate the ability of QAPV to prevent the clinically observed events.. We analyzed those reported events which were related to inconsistencies between DICOM RT plan parameters between the intended treatment (treatment planning system) and the delivered treatment (treatment machine). Critical DICOM RT plan parameters were identified. Each event was scored for importance using the Failure Mode & Effects Analysis (FMEA) methodology. Potential error occurrence (frequency) was derived based on the collected event data, along with the potential event severity, and probability of detection with and without the theoretical implementation of QAPV plan comparison check. FMEA Risk Priority Numbers (RPNs) with and without QAPV were compared to quantify the potential benefit of clinical implementation of QAPV. This analysis considered the highest risk parameters with RPN>200. Results: The clinical implementation of the IHE‐RO QAPV reduced RPN scores to below 200 for 7 (out of 8) high‐risk parameters. For example, RPN values reduced from 324 to 108 for ‘beam MU' s’ inconsistencies, 288 to 96 for ‘treatment machine’ inconsistencies, 200 to 40 for ‘beam limiting device type’ inconsistencies, and 252 to 72 for ‘wedge’ inconsistencies. Conclusion: This analysis quantifies the value of the IHE‐RO QAPV implementation in clinical workflow. We demonstrate that although QAPV does not provide a comprehensive solution for error prevention in radiation therapy, it can have a significant impact on a subset of the most severe clinically observed events.