Evidence map›Paper›PMID 31098532›Full record

ArticleFuture healthcare journal2018

Clinician-directed improvement in the accuracy of hospital clinical coding.

Krsna Mahbubani, Fanourios Georgiades, En Lin Goh, Swathikan Chidambaram, Prasanthi Sivakumaran, Timothy Rawson, Sucharita Ray, Anita Hudovsky, Dipender Gill

Open access · greenAbstract read
In one paragraph

Article in Future healthcare journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.4field-weighted citation impact, top 5% of its field
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

13 citing papers in PubMed, 28 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Using Machine Learning Algorithms to Develop a Clinical Decision-Making Tool for COVID-19 Inpatients.International journal of environmental research and public health · 2021
    Article
  10. Article
  11. Article
  12. Article
  13. 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

9 authors at 4 institutions in 1 country.

Krsna MahbubaniSt Mary's Hospital, London, UK.
Fanourios GeorgiadesImperial College Healthcare NHS Trust, London, UK.
En Lin GohImperial College London, London, UK.
Swathikan ChidambaramImperial College London, London, UK.
Prasanthi SivakumaranImperial College London, London, UK.
Timothy RawsonImperial College London, London, UK.
Sucharita RayImperial College Healthcare NHS Trust, London, UK.
Anita HudovskyImperial College Healthcare NHS Trust, London, UK.
Dipender GillImperial College Healthcare NHS Trust, London, UK.
Imperial College Healthcare NHS Trust · GBImperial College London · GBThe London College · GBSt. Mary's Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

'Payment by results' (PbR) remuneration for healthcare services relies on the accurate conversion of diagnoses into Healthcare Resource Group (HRG) codes that are then reimbursed. Inconsistencies in documentation can result in inaccuracies in this process, with consequent implications for measuring activity, disease incidence and organisational performance. The aim of this study was to determine if clinician involvement increases accuracy in the coding of medical cases. Selected records of medical patients admitted to a London NHS trust between November and December 2016 were reviewed by a coding auditor and a clinician. Any changes to the codes and HRG tariff were noted. In total, 123 cases were considered. Changes in code were made on 68 instances, resulting in an overall increase in remuneration of £39,215; an average of £318 per patient. The primary HRG code was changed in 31 cases which accounted for £28,040 of the increase in tariff. In conclusion, clinician involvement can help with documentation ambiguities, thus improving the accuracy of the coding process in a medical setting. Although such collaborative working offers advantages for both the clinician and the coding team, further work is required to investigate the feasibility of this recommendation on a larger scale.

Indexed as

clinical codingPayment by resultsPROCESSES AND SYSTEMS

Identifiers

PMID31098532
PMCPMC6510043
OpenAlexW2785468055

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.