In healthcare, randomised controlled trials (RCTs) remain a critical tool for resolving treatment uncertainties, yet they are still too infrequent and limited in scale to address the majority of clinical questions, according to experts. RCTs provide robust evidence on the outcomes of different interventions, including scenarios where no treatment at all may be considered. However, the current scarcity of large-scale trials means many patients continue to receive treatments whose benefits and risks are not fully understood.

Professor Michael Clarke of the Centre for Public Health at Queen’s University Belfast emphasizes the need for more frequent and expansive RCTs, highlighting landmark studies that have altered medical practice. These include trials demonstrating the benefit of aspirin after heart attacks, the life-saving role of steroids in severe Covid-19 cases, and the superiority of endovascular coiling over neurosurgical clipping for certain types of brain bleeds. Despite such advances, similar high-quality evidence is lacking for many other conditions.

To address this gap, Clarke proposes integrating a "randomisation button" within electronic health records. This tool would allow clinicians and patients facing a choice between two or more comparable treatments to randomly assign one option. The outcomes could then be tracked systematically, creating large, pragmatic trials embedded directly in routine care. Such a system could rapidly accumulate data on widely used treatments—whether prescribing antihypertensive medications, choosing chemotherapy regimens, or selecting wound dressings—thereby expediting the transition from uncertainty to reliable evidence.

Implementing this approach would require concerted efforts not only within the medical community but also support from political, clinical, and ethical stakeholders. If realized, it has the potential to produce some of the largest RCTs ever conducted, improving clinical decision-making while enhancing patient outcomes on a broad scale.

Professor Clarke argues that embracing this methodology could reduce premature deaths, minimize ineffective treatments, and ultimately improve healthcare delivery worldwide by systematically resolving longstanding uncertainties.