LAUSR

The diversity of diseases in rheumatology and variability in disease prevalence necessitates greater data parity in disease presentation, treatment responses including adverse events to drugs and various co-morbidities. Randomized Controlled Trials (RCTs) are the gold standard for drug development and performance evaluation. However, when the drug is applied outside the controlled environment the outcomes may differ in patient population. In this context, the need to understand the macro and micro changes involved in disease evolution and progression becomes important and so is the need for harvesting and harnessing the Real-World Data (RWD) from various resources to use them in generating Real World Evidence (RWE). Digital tools with potential relevance to rheumatology can be potentially leveraged to obtain greater patient insights, greater information on disease progression and disease micro processes and even in the early diagnosis of diseases. Since the patients spend only a minuscule proportion of their time in hospital or in a clinic, using the modern digital tools to generate realistic, bias proof RWD in non-invasive patient friendly manner becomes critical. In this review we have appraised different digital mediums and mechanisms for collecting RWD and proposed digital care models for generating RWE in rheumatology.