The revelation that University Hospitals of North Midlands (UHNM) removed more than a thousand patients from its waiting list using retrospective referral criteria and an AI system has reignited debate over how technology is deployed in patient care. The Trust insists a clinical review found “no significant harm,” yet local GPs, who described the move as “disruptive and unsafe,” have voiced deep concern about the process and its implications for clinical oversight.
On paper, the rationale is clear. The NHS faces record backlogs, limited resources, and ongoing pressure to improve access and efficiency. AI tools and data-driven systems promise to help identify priorities, streamline referrals, and support recovery targets. But when algorithms begin determining who remains on or is removed from a waiting list, efficiency and ethics intersect in complex and often uncomfortable ways.
Retrospective application of new referral rules does not simply clean data; it alters the clinical record of who once qualified for care. Each removed name represents a person whose symptoms once warranted attention. To make such determinations through automated systems, even with good intentions, risks reducing care to calculation and eroding public confidence in clinical decision-making.
This is not an argument against digital innovation. It is an argument for responsible use. AI must support, not replace, clinical judgement. The key questions are not just “Was harm done?” but “Was consent informed?”, “Were clinicians consulted?”, and “Can these systems explain their reasoning?”
As the NHS advances its digital and data ambitions, the UHNM experience is a timely reminder that governance and transparency must evolve alongside innovation. Technology can accelerate recovery, but trust will remain the foundation of every system that seeks to deliver care.
