296
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

Identifying user assistance systems for radiotherapy to increase efficiency and help saving lives

, ORCID Icon, &
Pages 318-336 | Received 07 Oct 2019, Accepted 24 Jul 2020, Published online: 30 Aug 2020
 

ABSTRACT

Increasing efficiency and reducing risk in radiotherapy cancer treatment is of high importance. User assistance systems within a digitally connected radiotherapy environment can support all involved professionals to perform their individual tasks faster and better. This paper presents a qualitative analysis of radiotherapy workflows and a corresponding process modelling in order to identify hypothetical user assistance systems for specific process activities. In addition, the results of an empirical study on the identified systems are presented together with derived requirements and design principles for these systems. A structured online survey with 50 medical physicists in Germany has been conducted. Among others the acceptance, the increase of perceived efficiency and the risk reduction while using the assistance systems are analysed and discussed. The results support the creation of value adding user assistance systems for radiotherapy that improve efficiency, reduce treatment risks and reach high user acceptance levels.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 269.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.