Systemic Lupus Erythematosus (SLE) Studies
Systemic lupus erythematosus (SLE) is characterized by an aggregation of symptoms, which can vary from patient to patient and make diagnosis difficult. This variability in the manifestation of the disease can also increase the complexity of screening and data collection during research studies, ultimately posing several unique challenges for your patients, your research sites, your study teams, and other stakeholders.
At Clinical Ink, we used the core technology of our eSource ecosystem to create the electronic Lupus Assessment Suite (eLAS™), the industry’s first data capture system specifically designed as a scalable solution to streamline lupus clinical trials. eLAS complements the site workflow, guiding the investigator through the completion of the questionnaires, eliminating duplicative data entry, and automatically suggesting scores and grades based on the data entered.
Since its inception, eLAS has been implemented widely:
An eLAS visit begins with the completion of a physical assessment where SLE-related symptoms are recorded. This triggers the completion of the required sections of the BILAG, SLEDAI, and CLASI questionnaires. Rather than having to transcribe the same data for all three questionnaires, as is typically required, eLAS automatically flows the data from the physical assessment to the required organ system forms and summaries, saving time and eliminating error.
The system makes it easy to:
- Display data from previous visits automatically, providing the investigator with the context required to evaluate the patient’s current status
- Make real-time edit checks, revealing potential inconsistencies between current and previously entered data
- Access information — like medical history, concomitant medications, notes, joint counts, physician global assessment, etc. — remotely, in real time, to determine if the patient qualifies for the study
- Reduce queries, expediting those that remain with a faster close rate because of the abundance of supporting documentation
- Alert monitors and data reviewers when specific criteria are met (e.g., scores outside a given range or scores that differ from previous scores by a specified amount) using the eSource ecosystem’s targeted source data review (tSDR)