Unit:
Κατεύθυνση Πληροφορική στην ΙατρικήΠληροφορική
Author:
Georgiadou Eleni
Poultsaki Maria
Supervisors info:
Κανδαράκης Ιωάννης, Καθηγητής, Τμήμα Μηχανικών Βιοϊατρικής, Πανεπιστήμιο Δυτικής Αττικής
Original Title:
Βελτίωση της ακτινοθεραπευτικής πράξης μέσω υπολογιστικών μοντέλων διαχείρισης ανθρωπίνων παραγόντων
Translated title:
Improvement of radiotherapy through computational management models of human factors
Summary:
In recent years, new and advanced technologies have radically changed the programming and implementation of radiotherapy. With the development of multi-leaf collimator (MLC), intensity-modulated radiotherapy (IMRT) and image-guided radiotherapy (IGRT) provides a more strictly defined target volume while minimising doses to critical organs.
However, the treatment process has become more complex and in order to improve patient safety and the quality of treatment, the radiotherapy industry has largely focused on the creation of new radiation delivery devices and new IT systems. While these new technologies improve the quality of radiotherapy and reduce errors in irradiation, they have created new sources of errors.
Recently developed recording and verification systems (R & V) to ensure accuracy in the delivery of therapeutic plans are often associated with usability issues that can lead to errors. This demonstrates the great need to improve interaction between users and technologies.
However, most technology assessments focused on improving techniques and technologies and limited studies looked at the role the human factor plays in patient safety.
Therefore, this study aims to implement human factor mechanisms to identify the unsafe parameters of an radiotherapy system and to provide recommendations on the issues arising from these errors. More specifically, it is divided into four phases:
• Review of events in radiotherapy.
• Workflow analysis. Unified Modeling Language (UML) activity diagrams
• Analysis of quantitative research factors
• Heuristic evaluation. Systematic inspection of user interfaces based on a set of user principles and recommendations
Main subject category:
Technology - Computer science
Keywords:
KEYWORDS: Radiotherapy, Machine learning, Data workflow, Human factor, Patient safety, Radiation protection, Error in radiation therapy, Linear accelerator
