Evidence map›Paper›PMID 35154414›Full record

ArticleShoulder & elbow2022

Surgeon involvement in clinical coding to improve data accuracy and remuneration in a shoulder and elbow unit.

Steven Kyriacou, David Butt, Will Rudge, Deborah Higgs, Mark Falworth, Addie Majed

Abstract read
In one paragraph

Article in Shoulder & elbow, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

6 authors.

Steven KyriacouShoulder and Elbow Unit, The Royal National Orthopaedic Hospital, Middlesex, UK.ORCID https://orcid.org/0000-0003-3813-9799
David ButtShoulder and Elbow Unit, The Royal National Orthopaedic Hospital, Middlesex, UK.
Will RudgeShoulder and Elbow Unit, The Royal National Orthopaedic Hospital, Middlesex, UK.
Deborah HiggsShoulder and Elbow Unit, The Royal National Orthopaedic Hospital, Middlesex, UK.
Mark FalworthShoulder and Elbow Unit, The Royal National Orthopaedic Hospital, Middlesex, UK.
Addie MajedShoulder and Elbow Unit, The Royal National Orthopaedic Hospital, Middlesex, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical coders are dependent on clear data regarding diagnoses and procedures to generate an accurate representation of clinical activity and ensure appropriate remuneration is received. The accuracy of this process may potentially be improved by collaboration with the surgical team.

methodsBetween November 2017 and November 2019, 19 meetings took place between the Senior Clinical Fellow of our tertiary Shoulder & Elbow Unit and the coding validation lead of our Trust. At each meeting, the Clinical Fellow assessed the operative note of cases in which uncertainty existed as to the most suitable clinical codes to apply and selected the codes which most accurately represented the operative intervention performed.

resultsOver a 24-month period, clinical coding was reviewed in 153 cases (range 3-14 per meeting, mean 8). Following review, the clinical coding was amended in 102 (67%) of these cases. A total of £115,160 additional income was generated as a result of this process (range £1677-£15,796 per meeting, mean £6061). Only 6 out of 28 (21%) cases initially coded as arthroscopic sub-acromial decompressions were correctly coded as such. DISCUSSION: Surgeon input into clinical coding greatly improves data quality and increases remuneration received for operative interventions performed.

Indexed as

clinicalCodingdataremunerationvalidation

Identifiers

PMID35154414
PMCPMC8832715

What OpenQuestion holds

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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.