Web-based eHealth Clinical Decision Support System as a tool for the treat-to-target management of patients with systemic lupus erythematosus: <i>development and initial usability evaluation</i>.
case_series · Level IV
Where this comes from
- Record sourced from PubMed, PMID 37751942.
- Also identified by DOI 10.1136/bmjhci-2023-100811 and PMC identifier 10533702.
- Licence recorded as CC BY-NC.
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Abstract
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. 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. 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. 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. 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.
Medical subject headings
- Decision Support Systems, Clinical
- Mobile Applications
- Lupus Erythematosus, Systemic
- Telemedicine