PO.8.186 SLE-T2T – a digital treat-to-target clinical decision support system for the management of systemic lupus erythematosus patients: development and usability evaluation. (27th September 2022) - Parra Sanchez, A; Grimberg, MG; Hanssen, MMA; Aben, MO; Jairth, EE; Dhoeme, PS; Tsang-A-Sjoe, M; Voskuyl, A; Leopold, JH; Van Vollenhoven, R
Abstract : Purpose: We aimed to design and develop a first prototype of SLE-T2T, an online clinical decision support system (CDSS) tool, and test its usability for the implementation of a treat-to-target strategy in the management of patients with SLE. Methods: SLE-T2T was conceived as a web-based application with a specific task – to generate appropriate treatment advice based on entered patients data. A general sketch of the program was made, and general consensus was achieved with regards to the desired functionalities. In the development phase, a beta version of SLE-T2T was conceived using a free integrated development environment, and based on Javascript, HTML and CSS. After, the system was hosted temporarily on the website of the Amsterdam Rheumatology & Immunology Center, to be accessible for the participants in evaluation phase. Finally, a System Usability Score Survey (SUS) was chosen as the usability test tool, given its simplicity and advantages; coupled with unstructured feedback collected using the think aloud method to determine whether the CDSS was user-friendly, comprehensible, easy-to-deliver, and workflow-oriented. Results: The SLE-T2T web-based system developed, consisted of: (1) an input scheme with the set of indexes and scores existing for the measurement of SLE disease activity (cSLEDAI-2K, SLEDAI-2K, PGA score) as well as the patients' medication; (2) a rule-based interface that collects and processes patients data, and (3) an output dashboard with the generated set of recommendations tailored for the patients clinical state and aiming to reach a pre-stablished target of treatment (figure 1). In the interim usability and acceptability evaluation, 7 participants completed the SUS survey. The mean usage time for SLE-T2T was 8 minutes. On a scale of 0 (worst) to 100 (best), the median SUS score of SLE-T2T was 79, categorizing the application as 'good' and indicating the need for minor improvements to the design necessary to reach a final version for later implementation in a treat-to-target pilot study. Conclusions: SLE-T2T is the first eHealth tool to be designed for the management of SLE patients in a treat-to-target context. The SUS score and unstructured feedback showed high acceptance of this digital instrument.