Gary Ezzell1, Bhisham Chera2, Adam Dicker3, Eric Ford4, Louis Potters5, Lakshmi Santanam6, Sheri Weintraub7. 1. Department of Radiation Oncology, Mayo Clinic Arizona, Phoenix, Arizona. Electronic address: ezzell.gary@mayo.edu. 2. Department of Radiation Oncology, University of North Carolina School of Medicine, Chapel Hill, North Carolina. 3. Department of Radiation Oncology, Jefferson Medical College of Thomas Jefferson University, Philadelphia, Pennsylvania. 4. Department of Radiation Oncology, University of Washington, Seattle, Washington. 5. Department of Radiation Oncology, Department of Radiation Medicine, Northwell Health, Lake Success, New York. 6. Department of Radiation Oncology, Washington University, St. Louis, Missouri. 7. Department of Radiation Oncology, Southcoast Hospitals Group, Fairhaven, Massachusetts.
Abstract
PURPOSE: The Radiation Oncology Incident Learning System (RO-ILS) receives event reports from facilities across the country. This effort extracted common error pathways seen in the data. These pathways, expressed as fault trees, demonstrate the need for, and opportunities for, preventing these errors and/or limiting their propagation to treatment. METHODS AND MATERIALS: As of the third quarter of 2016, 2344 event reports had been submitted to RO-ILS and reviewed. A total of 396 of the reports judged highest priority were rereviewed and assigned up to 3 keywords to classify events. Based on patterns among the keyword assignments, the data were further aggregated into pathways leading to 3 general error types: "problematic plan approved for treatment," "wrong shift instructions given to therapists," and "wrong shift performed at treatment." Fault trees were created showing how different errors at different stages in the treatment process combine to flow into these general error types. RESULTS: A total of 173 of the 396 (44%) events were characterized as belonging to 1 of these 3 general error types. Ninety-nine events were defined as "problematic plan approved for treatment," 40 as "wrong shift instructions given to therapists," and 34 as "wrong shift performed at treatment." Seventy-six of these events (44%) resulted in incorrectly delivered treatment. Event discovery was by therapists (n = 76), physicists (n = 45), physicians (n = 23), dosimetrists (n = 15), or not identified (n = 9); 5 events were found as a result of the patient questioning the staff. For the event type "problematic plan approved for treatment," 64 of the 99 (65%) events were attributable to physician error: incorrect target or dosing pattern prescribed. CONCLUSIONS: Data extracted from RO-ILS event reports demonstrate common error pathways in radiation oncology that propagate all the way to treatment. Additional study and coordination of efforts is needed to develop and share best practices to address the sources of these errors and curtail their propagation.
PURPOSE: The Radiation Oncology Incident Learning System (RO-ILS) receives event reports from facilities across the country. This effort extracted common error pathways seen in the data. These pathways, expressed as fault trees, demonstrate the need for, and opportunities for, preventing these errors and/or limiting their propagation to treatment. METHODS AND MATERIALS: As of the third quarter of 2016, 2344 event reports had been submitted to RO-ILS and reviewed. A total of 396 of the reports judged highest priority were rereviewed and assigned up to 3 keywords to classify events. Based on patterns among the keyword assignments, the data were further aggregated into pathways leading to 3 general error types: "problematic plan approved for treatment," "wrong shift instructions given to therapists," and "wrong shift performed at treatment." Fault trees were created showing how different errors at different stages in the treatment process combine to flow into these general error types. RESULTS: A total of 173 of the 396 (44%) events were characterized as belonging to 1 of these 3 general error types. Ninety-nine events were defined as "problematic plan approved for treatment," 40 as "wrong shift instructions given to therapists," and 34 as "wrong shift performed at treatment." Seventy-six of these events (44%) resulted in incorrectly delivered treatment. Event discovery was by therapists (n = 76), physicists (n = 45), physicians (n = 23), dosimetrists (n = 15), or not identified (n = 9); 5 events were found as a result of the patient questioning the staff. For the event type "problematic plan approved for treatment," 64 of the 99 (65%) events were attributable to physician error: incorrect target or dosing pattern prescribed. CONCLUSIONS: Data extracted from RO-ILS event reports demonstrate common error pathways in radiation oncology that propagate all the way to treatment. Additional study and coordination of efforts is needed to develop and share best practices to address the sources of these errors and curtail their propagation.
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