How do real-world data compare with randomized controlled trial data obtained from clinical research trials?
Randomized controlled trials are considered the “gold standard” for determining whether treatments or interventions are effective. However, these trials include relatively small patient populations that represent only a fraction of a disease population. The data derived from these clinical trials are often used to acquire regulatory approval for new drugs or interventions that make them readily available for patients.
By contrast, real-world evidence provides insights on treatment outcomes, for real people in real-world environments, outside of tightly controlled, unnatural clinical trial settings accounting for such variables as age, gender, race and comorbidities, and the results pertain to a much larger, heterogenous patient population.
Medical decision-making with and without clinical trial studies
Scenario A: Patient presents to the ED with chest pain. The medical team assesses him for a possible heart attack and orders vital signs, an EKG and labs. The patient is diagnosed with a heart attack and is treated with interventions recommended by long-standing clinical research.
Scenario B: Patient presents to the ED with fever, cough and shortness of breath. The medical team assesses him for one of several lung conditions but rules out common diagnoses and classifies patient as ‘suspected COVID-19’. Patient’s health begins to deteriorate. With no clinical research trial data, the physicians have 2 choices to determine the most efficacious treatment plan:
- Assess anecdotal evidence from colleagues that’s based on limited experience and lacks reliable and statistical value
- Analyze real-world data based on current prescribing patterns and the resulting outcomes across distinct patient subgroups