Evidence map›Paper›PMID 41841079›Full record

ArticleCureus2026

Are We Truly Addressing the Elective Surgery Backlog?

Daniel Jones, Maulik Gandhi

Abstract read
In one paragraph

Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Daniel JonesTrauma and Orthopaedics, Bradford Royal Infirmary, Bradford, GBR.
Maulik GandhiOrthopaedics, Bradford Royal Infirmary, Bradford, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

accurate databacklogcodingelective surgerywaiting time

Identifiers

PMID41841079
PMCPMC12989084

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.