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Development of a quality assurance system in radiation oncology: A 12-year experience in a University Hospital
Wannapha Nobnop1,2, Vicharn Lorvidhaya1,2, Somsak Wanwilairat1,2
1Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Purpose:
This study aimed to report 12 years of experience in the development of a quality assurance system in radiation oncology in a university hospital.
Material And Methods:
We developed the Quality Assurance Program in Radiation Oncology (QUAPRO) in 2008 to detect treatment deviation in the radiotherapy (RT) process with three steps of near-miss detection: simulation and prescription (primary check, PC), treatment planning (secondary check, SC), and treatment delivery process (tertiary check, TC). We transferred our paper-based medical records to electronic-based radiotherapy information systems (RTISs) in 2013. QUAPRO was completely integrated into RTIS in 2017. Since then, electronic-based incident reporting has been conducted. The program is called the Radiation Incident Learning System (RILS). The near-miss rates were compared during the three time periods: 2008-2012, 2013-2017, and 2017-2020.
Results:
Five years of paper-based QUAPRO for 2008-2012 demonstrated a fluctuation in the checking ratio, with a gradually increasing rate of near misses of 3.5-19.7%. After electronic-based medical records were developed in 2013, the results revealed a dramatic increase from a rate of 2.7 to 4.2 in the number of checks per patient and achieved an increased rate of near misses of 24.7% for PC, SC, and TC. The rate of near misses gradually decreased to 5.3% after 2017 because of RT workflow improvement.
Conclusion:
The analysis of 12 years in near-miss data reflected the effectiveness of our quality assurance program. The QUAPRO system can detect near-miss incidents in the whole RT workflow and illustrate the detection improvement when integrated into electronic-based medical records. Regular feedback and exploration of near-miss reporting are recommended for proper RT workflow improvement.
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