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Objective: To identify and quantify key factors driving the decline in efficiency of NHS elective care, focusing on medical workforce dynamics, resource allocation and systemic inefficiencies. We hypothesised that medical workforce sickness absence and administrative turnover significantly affect productivity and backlog growth, instead medical workforce turnover has not effect. Design: This research is a national retrospective observational study using monthly panel data from NHS Digital (January 2018–December 2023). Ordinary Least Squares regression and Generalised Method of Moments models were applied to estimate the impact of workforce and resource factors on productivity and backlog indicators. These methods will account for the unobserved factors and potential reverse causality problem. Setting: The study follows secondary care across all NHS Trusts in England, with performance measured at the Trust level. Participants: All NHS Trusts delivering elective surgical services between January 2018 and December 2023. The unit of analysis was Trust-month observations, encompassing all elective surgical patients treated in each Trust. Main outcome measures: (1) Average per capita completed surgery elective cases (proxy for productivity). (2) Ratio of incomplete elective surgery to average completed elective surgery cases (proxy for additional resources needed to meet demand). Results: A one-percentage-point increase in NHS medical workforce sickness rates was associated with a 4.4% decrease in average completed elective cases (95% CI −0.0598 to −0.0272, p  < 0.05). Gains in administrative staff reduced excess elective surgery incomplete cases by 14.4% (95% CI −0.155 to −0.133, p  < 0.05). Findings were robust to controls for other workforce and resource-related variables. Conclusions: Workforce expansion alone will not resolve NHS elective surgery backlogs. Reducing medical sickness absence, enhancing staff wellbeing and ensuring adequate administrative capacity are critical to improving productivity and reducing waiting times.

More information Original publication

DOI

10.1177/01410768261442040

Type

Journal article

Publisher

SAGE Publications

Publication Date

2026-04-21T00:00:00+00:00