Why Is the NHS Treating Fewer Patients With More Staff?

The NHS employs more people than at any point in its history. Full-time equivalent staff numbers in NHS England exceeded 1.3 million in 2024, up from 1.1 million in 2019 — a 17% increase in five years. Yet the total output of the NHS — measured as weighted activity across elective surgery, emergency admissions, outpatient appointments, community care, and mental health contacts — has not increased proportionally. The productivity index, set at 100 for 2014, stood at 96.8 in 2024. More staff, less output per person. This is the central efficiency puzzle facing the health service.

COVID caused a genuine structural break. The pandemic reduced NHS productivity by nearly 20% in 2020 through cancellation of elective care, infection control measures that reduced theatre throughput, social distancing in clinical areas, and staff absence. Four years later, the recovery is incomplete. Output per worker in 2024 stood at 90.3 on the index — still nearly 10% below 2014 levels. Some of this reflects persistent infection control requirements. Some reflects higher acuity of patients presenting after delayed care during the pandemic. And some reflects structural factors that predate COVID: ageing IT systems, estate constraints, and clinical pathways designed decades ago.

The political sensitivity of productivity in the NHS is high. Discussions are often framed as blaming frontline staff, which they should not be. Individual clinicians and nurses are, by and large, working as hard as or harder than before. The productivity gap is a system-level phenomenon: it reflects how work is organised, what technology is available, how estates are configured, and what administrative burden falls on clinical staff. A surgeon who spends 30 minutes per case in theatre but whose list is cut from 6 to 4 cases because of cleaning protocols between patients is not less productive as an individual — but the system output has fallen.

The Lord Darzi review of the NHS (2024) identified productivity as a central challenge and recommended a 10-year programme of investment in digital infrastructure, reform of clinical pathways, and reduction of bureaucratic burden. The review estimated that closing the productivity gap to pre-COVID levels alone would be equivalent to treating 1.5 million additional patients per year without any additional spending. The government’s response, the Elective Recovery Plan, set targets for increasing elective throughput, but meeting those targets while addressing the 7.5-million-strong waiting list requires productivity gains that have not yet materialised at scale.

International comparison is instructive but imperfect. Germany, France, and the Netherlands all saw similar COVID-era productivity drops but have recovered faster, in part because they had higher baseline capital investment in hospital infrastructure and digital systems. The UK spends significantly less per capita on health capital than the OECD average, and the maintenance backlog in NHS buildings has tripled in a decade. Productivity measurement in healthcare is itself contested: the ONS methodology attempts to quality-adjust output (counting improved survival and patient experience as outputs), but the adjustments are incomplete and lag behind real-time activity data.