Organic generation of real-world real-time data for clinical evidence in radiation oncology. (December 2020)

• Record Type: Journal Article
• Authors: Bertolet, A.; Wals, A.; Miras, H.; Macías, J.
• Is Part Of: International journal of medical informatics. Volume 144(2020)
• Publication Date: 2020-12
• Subjects: radiotherapy -- radiation oncology -- oncology information systems -- real-world data -- structured data -- electronic medical records; Medical informatics -- Periodicals; Information science -- Periodicals; Computers -- Periodicals; Medical technology -- Periodicals; Medical Informatics -- Periodicals; Technology, Medical -- Periodicals; Computers; Information science; Medical informatics; Medical technology; Electronic journals; Periodicals; Electronic journals; 610.285
• DOI: 10.1016/j.ijmedinf.2020.104301
• Languages: English
• ISSNs: 1386-5056

Abstract

Highlights: We present an approach to use OISs in radiation oncology in a paperless and optimized way, with the design of a workflow connected through automated routines. Our work allows for generation of real-world data to feed the need for clinical evidence in an effortless way once the system is implemented. Centralization of all the information in a single source also points towards an increased satisfaction of the personnel and further optimization of the department performance based on statistics. Abstract: Purpose: We introduce a system devoted to automatically produce structured data in radiotherapy to: (i) relate clinical outcomes with any variable; and (ii) optimize resources and procedures. Methods and material: We have designed a detailed workflow for a patient to follow during radiotherapy treatments. Four elements of Oncology Information Systems (OISs) can be mainly interrelated in our system: (a) task lists to be accomplished by the staff; (b) forms to fill in at each step of the workflow; (c) generation of reports; and (d) a system to trigger new tasks, forms or reports when an needed, either automatically or manually. We handle the data dumped into reports with Visual Basic for Word code to store structured data for patients in electronic medical records (EMRs). These EMRs can be further analyzed, generating clinical real-world data in real time, i.e., at any step of the process. Results: Our system was implemented about the beginning of 2019, producing a database filled with a pool of 1, 184 patients in a year. Although one year is not long enough to produce statistically clinical outcomes, we show our results for cancer by anatomical location so far to meet the first goal stated above. With respect to the second goal, we here (1) show the distribution of times taken for the whole radiotherapy process divided by anatomical locations for, (2) study the fractionations schemes used throughout 2019, and (3) evaluate the number of missed sessions of treatment in our institution. Our system also leads to better communication among staff members, dramatically reducing misunderstandings because of the centralization of the information. Conclusions: We present an integrated customization of an OIS, yet adaptable to others, that makes possible an optimized performance of the department by driving an automatized paperless workflow; and allows for an automatized and effortless collection of structured data throughout the radiotherapy process.