Web-based eHealth Clinical Decision Support System as a tool for the treat-to-target management of patients with systemic lupus erythematosus: Development and initial usability evaluation

Agner Russo Parra Sanchez, Max G. Grimberg, Myrthe Hanssen, Moon Aben, Elianne Jairth, Prishent Dhoeme, Michel W. P. Tsang-A-Sjoe, Alexandre Voskuyl, Hendrik Jan Jansen, Ronald van Vollenhoven

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Background Treat-to-target (T2T) is a therapeutic strategy currently being studied for its application in systemic lupus erythematosus (SLE). Patients and rheumatologists have little support in making the best treatment decision in the context of a T2T strategy, thus, the use of information technology for systematically processing data and supporting information and knowledge may improve routine decision-making practices, helping to deliver value-based care. Objective To design and develop an online Clinical Decision Support Systems (CDSS) tool "SLE-T2T", and test its usability for the implementation of a T2T strategy in the management of patients with SLE. Methods A prototype of a CDSS was conceived as a web-based application with the task of generating appropriate treatment advice based on entered patients' data. Once developed, a System Usability Score (SUS) questionnaire was implemented to test whether the eHealth tool was user-friendly, comprehensible, easy-to-deliver and workflow-oriented. Data from the participants' comments were synthesised, and the elements in need for improvement were identified. Results The beta version web-based system was developed based on the interim usability and acceptance evaluation. 7 participants completed the SUS survey. The median SUS score of SLE-T2T was 79 (scale 0 to 100), categorising the application as 'good' and indicating the need for minor improvements to the design. Conclusions SLE-T2T is the first eHealth tool to be designed for the management of SLE patients in a T2T context. The SUS score and unstructured feedback showed high acceptance of this digital instrument for its future use in a clinical trial.
Original languageEnglish
Article numbere100811
JournalBMJ Health and Care Informatics
Volume30
Issue number1
DOIs
Publication statusPublished - 26 Sept 2023

Keywords

  • decision support systems, clinical
  • disease management
  • medical informatics
  • outcome assessment, health care

Cite this