Computer automation for physics chart check should be adopted in clinic to replace manual chart checking for radiotherapy

摘要

In 1994, American Association of Physicists in Medicine (AAPM) task group (TG) report 40 established that plan check and chart review is part of medical physics major responsibilities.1 As the treatment technique complexity increases, patients’ plan check and chart review becomes more critical to treatment accuracy and patient safety, yet more cumbersome as the checking items increase dramatically. AAPM published two scientific reports in 2020 specifically to address the efficiency strategies and minimum requirements.2, 3 Both reports discussed the benefits of computer automation in reducing human labor and improving process efficiency, whereas they also emphasized the difficulty and limitation of implementing computer-aided programs for various clinical practices. There poses a dilemma that computer-automation can save clinical physicists’ time, while implementing a computer-aided chart check program requires high standardization in nomenclature and continuous maintenance to accommodate ever-changing technology and various clinical workflows. This article debates on the proposition “Computer automation for physics chart check should be adopted in clinic to replace manual chart checking for radiotherapy.” Herein, we have Mr. Edward Clouser argues for the proposition whereas Dr. Quan Chen argues against the proposition. Mr. Clouser received M.S. in Physics in 2003 from Cleveland State University. He received his clinical training as a medical physicist at the Cleveland Clinic and stayed on faculty post-graduation. He has worked at the Mayo Clinic in Arizona for 14 yr, among which he has been serving as the program director of the Medical Physics Residency for 7 yr. His current interests include developing tools to automate clinical work including chart review and weekly checks for dosimetrists and physicists. He holds the rank of Assistant Professor of Radiation Oncology in the Mayo School of Medicine and is board certified by the American Board of Radiology. Dr. Chen received his PhD in Medical Physics from the University of Wisconsin-Madison in 2004. He started his career in industry as a senior research physicist at Tomotherapy before joining University of Virginia in 2011. Currently he is an Associate Professor at University of Kentucky. His research interests cover a wide range of topics include dose calculation algorithms, motion management, adaptive therapy, kV dosimetry, innovative quality assurance method, as well as Artificial Intelligence (AI). He has cofounded a company (Carina Medical LLC) to develop AI-based applications for Radiation Oncology. Dr. Chen has also developed many clinical tools that was in use at different centers to improve the safety and efficiency of clinical services. Dr. Chen is an Associate Editor of journal of applied clinical medical physics (JACMP) and serves on several committees at AAPM. Chart checking has long been a primary task of clinical medical physicists in the process of ensuring treatment planning integrity. Historically, we would look through a paper chart and maybe a few printed pages from the treatment planning system to verify adherence to general planning rules and finding transcription errors. The concepts of a chart check are held in the individual physicist’s head and the effectiveness in identifying errors are mostly based on individual physicist’s experience and attention to details. As the radiation oncology treatment planning and delivery technologies evolve to a rather high level of complexity, chart checking requires a far more complicated and organized venture. Thanks to digital imaging and communications in medicine (DICOM) file standardization, record and verify systems, and other software advances, patients’ detailed treatment data can be created, transferred, and delivered in a rather secure and integrated manner. Manual transcription errors for plan and machine settings should be nearly extinct. In a single vendor environment for oncology information system (OI