Evidence map›Paper›PMID 39273807›Full record

ArticleHealthcare (Basel, Switzerland)2024

Achieving Robust Medical Coding in DRGs Systems: Innovative Actions Adopted in Greece.

Charalampos Platis, Leonidas Papaioannou, Panagiota Sideri, Pantelis Messaropoulos, Konstantinos Chalkias, Nikolaos Kontodimopoulos

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2024. 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. Review
  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.

Charalampos PlatisKETEKNY (Greek DRG Institute), 10677 Athens, Greece.
Leonidas PapaioannouKETEKNY (Greek DRG Institute), 10677 Athens, Greece.ORCID 0000-0002-1878-8364
Panagiota SideriKETEKNY (Greek DRG Institute), 10677 Athens, Greece.
Pantelis MessaropoulosKETEKNY (Greek DRG Institute), 10677 Athens, Greece.
Konstantinos ChalkiasKETEKNY (Greek DRG Institute), 10677 Athens, Greece.
Nikolaos KontodimopoulosSchool of Social Sciences, Hellenic Open University, 26335 Patras, Greece.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study is to evaluate and illustrate the effectiveness of a specialized digital platform developed to improve the accuracy of medical coding during the full implementation of Greece's new DRG system, and to highlight innovative actions for achieving and/or improving accurate medical coding. Already grouped DRG cases recorded in the first DRG implementation year in the region of Crete were examined. A sample of 133,922 cases was analyzed and audited, through a process consisting of three stages: (i) digitalization, (ii) auditor training, and (iii) control and consultation. The results indicated that a significant proportion of DRG coding, with a length of stay exceeding one day, was reclassified into different DRG categories. This reclassification was primarily due to coding errors-such as the omission of secondary diagnoses, exclusion of necessary medical procedures, and the use of less specific codes-rather than mistakes in selecting the principal diagnosis. The study underscores the importance of medical coding control and consulting services. It demonstrates that targeted actions in these areas can significantly enhance the implementation of the DRG coding system. Accurate medical coding is crucial for transparent allocation of resources within hospitals, ensuring that hospital services and reimbursements are appropriately managed and allocated based on the true complexity and needs of patient cases.

Indexed as

activity-based fundingartificial intelligencecodingdiagnostic-related groupdigital platformefficiencyhealth systemsinnovation

Identifiers

PMID39273807
PMCPMC11395024

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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.