Year: 2026
Type: article
Study design: Observational Study
Abstract: Background Orthopaedics currently has the largest waiting list of any surgical speciality in the UK, and the number of patients awaiting elective surgery is continuing to climb. This retrospective study aims to quantify the impact of coding errors on elective surgery waiting times at a large UK district general hospital. Method Data from 381 patients who underwent operations on elective orthopaedic operating lists between January 1, 2025, and March 31, 2025, were included in the study. Most orthopaedic patients with acute issues are operated on a dedicated acute list. However, surges in acute referrals may result in re-purposing of elective operating lists to treat acute patients. These cases are at risk of being incorrectly coded as elective operations. The electronic booking code of the operation was compared with the case notes of each patient to determine if the coding as elective or acute was accurate. Results Of the 381 patients coded as elective, 44 were acute cases falsely coded as elective. The mean waiting time for these false elective cases was 10.86 days, in comparison to 247.24 days for the true elective cases. Overall, incorrect coding of trauma cases as elective cases artificially reduced the mean waiting time by 27.14 days, or 11.01%. A Mann-Whitney U test showed this to be statistically significant (p = 0.012). Conclusion Inaccurate electronic coding substantially and artificially reduces orthopaedic surgery waiting time. This is likely driven by human error and software errors that can prevent correct coding. These issues might be addressed through a review of the approved Electronic Patient Record (EPR) software systems, staff training, and a further push towards cold-site operating to better separate acute and elective orthopaedic care. Finally, a multi-centre study would demonstrate how far-reaching these coding errors are.
Source: Cureus
Authors: Daniel Jones, Maulik Gandhi
Institution: Bradford Royal Infirmary
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W7128816424