Abstract

All Radiation Therapy Management System (TMS) hold detailed information on planned and delivered treatments, however, it can be time-consuming for multidisciplinary teams to access and structure treatment records in the optimal manner for efficient clinical practice and easy research due to limited reporting features. This study aims to develop a web-based application to rapidly and automatically retrieve treatment records of one or more patients, present the desired information to clinical and research staff, and remind them of upcoming treatment milestones, promoting safety, quality and efficiency of radiotherapy clinical practice. We developed a web-based application as a web portal for authorized users to query and retrieve, and present detailed information from the TMS in an optimal practice-specific manner. The tool is composed of two parts, a web app that runs in standard browsers, and a web server. The web app is developed using markup and interpreted computer programming languages, and initiates query requests for the treatment history. The web server is developed using a high-level interpreted programming language, hosted on an an open-source server. It receives requests from the browser-based app and queries data from the TMS database. The web app then shows the received data in a clinically-optimized form and highlights important upcoming milestones such as when the next on-treat-visit is due, or treatment completion summary is required. The queries can be based on physician, dose, machine, patient, technique, patient list, etc. The data shown to users includes basic patient demographics, diagnosis, prescription sites and their completed and scheduled total fractions, the delivered dose and scheduled total dose, the treatment start and end dates, etc. The plan file can be downloaded in PDF files for each approved prescription and rapidly displayed upon request. We developed an efficient tool for radiotherapy treatment history check. Its performance has been optimized such that it can query and analyze treatment data for an average of 141.2 patients with 546.5 sites per second. Since its clinical implementation, this tool has been widely used by our physicians, physicists, residents, and other clinic staff and researchers, and has been recognized as a very efficient and handy tool for them to quickly query data based on their needs without the tedious and time-consuming access of the TMS database through its native graphical user interface. This tool has improved the data processing and management of our department’s clinical and research practice, and will continue to be one of the most important tools used in our department. This tool was developed for an electronic patient information management system but can be easily expanded to provide the same function for other TMSs. It could bring beneficial changes to the current clinical practice – a step closer to a personalized/precision medicine.

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