Quantitative quality indicators and automated radiotherapy care paths - Capone, Luca; Di Minico, Debora; Pluchinsky, Ashley; Lusini, Federica; Gennuso, Leonardo; Triscari, Giulia; Cavallo, Francesca; Forte, Velia; Gennuso, Natascia; Mychkovsky, Martha; et al. (Journal of Biomedical Practitioners, 2021)
INTRODUCTION High quality standards are often the key for success in modern radiotherapy. The goal of this study is to assess automated and targeted care paths to define new quantitative quality indicators in radiation oncology and optimize the efficiency and safety of the services provided. MATERIALS AND METHODS For this study, two international cancer centers part of the same network (UPMC San Pietro in Rome (CC#1) and UPMC Villa Maria in Mirabella Eclano (CC#2)) have been involved, both equipped with a linear accelerator and a CT scan. The data reviewed refers to a period between January 2019 and December 2019. Following the workflow of both centers during electronic medical record data input, we created automated models adaptable to the different types of treatment and customizable for each patient. Using the ARIA v15 (Varian Medical System, CA, Palo Alto, USA) software, we converted the various steps of the care path in modules that can be connected to create the patient’s care process. Care paths are therefore modules of an automated process consisting of tasks and appointments, with well-defined execution times within which they must be completed electronically. To obtain quantitative information on both centers we focused on three factors: tasks completed in relation to their execution times, number of days, and staff compliance with the automated system. RESULTS Measuring the completed tasks allows to define the compliance of the automated process with the care paths, whereas the time required to complete the tasks helps identify areas for improvement. Within this study timeouts are always performed on time, but peer review and treatment approval outcomes are unsatisfactory. A defined delay time allows to keep track of tasks in a precise manner and reviewing these values in both centers helps us understand if the task delivery time is appropriate or if there is room for improvement. All analyzed data show that the percentage of tasks completed in both centers and the completion times are different. CONCLUSIONS Automated care paths and their modules can be an effective and efficient tool to measure the tasks performed by a radiation oncology unit, especially if they are used as a tool of continuous quality improvement.