Evidence map›Paper›PMID 38689701›Full record

ArticleFuture healthcare journal2024

Targeted education for clinicians and clinical coding staff improves the accuracy of clinical coding: A quality improvement project.

Shiva T Radhakrishnan, Robert Perry, Surabhi Misra, Sucharita Ray, Aruchuna Ruban, Bernard I Quayson, Rishi Fofaria, Anita Hudovsky, Horace R T Williams

Abstract read
In one paragraph

Article in Future healthcare journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Exploring Current Procedural Terminology Codes for Physical Therapist Evaluations in the United States: Results of a Feasibility Study.Physiotherapy research international : the journal for researchers and clinicians in physical therapy · 2026
    Article
  5. Article
  6. Observational
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.

Shiva T RadhakrishnanClinical research fellow, Imperial College London, London, UK and gastroenterology specialist trainee, Imperial College Healthcare NHS Trust, London, UK.
Robert PerryClinical research fellow, Imperial College London, London, UK and gastroenterology specialist trainee, Imperial College Healthcare NHS Trust, London, UK.
Surabhi MisraMedicine for the elderly specialist trainee, Hillingdon Hospitals NHS Foundation Trust Uxbridge, UK.
Sucharita RayDeputy head of clinical coding Imperial College Healthcare NHS Trust, London, UK.
Aruchuna RubanGastroenterology consultant, Imperial College Healthcare NHS Trust, London, UK.
Bernard I QuaysonSenior clinical coding specialist, Imperial College Healthcare NHS Trust, London, UK.
Rishi FofariaGastroenterology consultant, West Hertfordshire Teaching Hospitals NHS Trust.
Anita HudovskyHead of clinical coding, Imperial College Healthcare NHS Trust.
Horace R T WilliamsHonorary clinical senior lecturer, Imperial College London, London, UK, and gastroenterology consultant Imperial College Healthcare NHS Trust, London.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The allocation of healthcare resources is reliant upon accurate information generated through clinical coding. Several factors contribute to coding inaccuracies, one of which is interpreting medical documentation. A lack of awareness among medical staff of the clinical coding process and the importance of detailed documentation exacerbates this problem. To investigate this further, 1 month of inpatient clinical coding data from a single hospital ward was reviewed by clinicians experienced in the coding and auditing process. If the reviewing clinician identified inaccuracies in the initial clinical coding, Healthcare Resource Group (HRG) codes were changed. Education sessions were then provided both to junior clinicians working on the hospital ward and to clinical coding staff and a further month of clinical coding data was again reviewed to assess for any difference after the sessions. HRG changes were made in 58.5% of 94 cases initially. Following the educational sessions, 20.5% of HRGs changed in 73 cases (p<0.0001), indicating more accurate initial clinical coding. There were also statistically significant reductions in the extent to which the primary and secondary diagnoses were changed. This study demonstrates that targeted education sessions for both junior clinicians and clinical coding staff can improve the accuracy of inpatient clinical coding.

Indexed as

Clinical codingEducationQuality improvement project

Identifiers

PMID38689701
PMCPMC11059275

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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.