Journal of cancer research and therapeutics · 2022
Development of a quality assurance system in radiation oncology: A 12-year experience in a University Hospital.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Nobnop Wannapha, Lorvidhaya Vicharn, Wanwilairat Somsak, Watcharawipha Anirut, Tharavichitkul Ekkasit, Onchan Wimrak, Chakrabandhu Somvilai, Klunklin Pitchayaponne, Jia-Mahasap Bongkot, Muangwong Pooriwat, Chitapanarux Imjai
Аннотация
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.
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.