Evidence map›Paper›PMID 39957851›Full record

ArticleNeurosurgery practice2024

Improving Quality Metrics in Neurosurgery: A Spinal Surgery 3-Year Case Review.

Christina Nicoll Feller, Erin M Bodenbach, Julie M Kolinski, Grant P Sinson

Abstract read
In one paragraph

Article in Neurosurgery practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Christina Nicoll FellerMedical College of Wisconsin, Milwaukee, Wisconsin, USA.ORCID https://orcid.org/0000-0001-7831-2854
Erin M BodenbachMedical College of Wisconsin, Milwaukee, Wisconsin, USA.
Julie M KolinskiDepartment of Medicine, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.
Grant P SinsonDepartment of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesDespite the known importance of accurate clinical documentation as a companion to quality patient care, this is not often prioritized in practice and leads to a variety of downstream consequences. Inaccurate documentation leads to missed opportunities in full, accurate coding. In turn, it also negatively influences hospital and physician quality ranking, medical center profiling, and revenue captured. The aim of this study is to highlight the opportunity for continuous improvement in clinical documentation and the significance accurate clinical documentation has on outcome measures, such as expected length of stay (eLOS).

methodsA single-center retrospective chart review took place for patients undergoing spinal surgery from 2019 to 2021. Based on Vizient's diagnosis-related group risk model for eLOS, 192 charts spanning 10 unique diagnosis-related groups were reviewed to identify ICD-10 diagnosis and procedure codes that were not coded or not clearly documented by a physician. A new eLOS for each patient was recalculated with the addition of the newly identified variables and then compared with the original eLOS.

resultsOverall, there was a significant difference between the original eLOS and new eLOS when the newly identified variables were added (

conclusionIncomplete documentation and coding can misrepresent the quality of patient care provided and the complexity of their cases. This represents an opportunity for improvement for both the clinicians, clinical documentation improvement specialists, and coders to improve quality metrics and hospital rankings.

Indexed as

Clinical documentationDRGNeurosurgeryQuality improvementSpinal surgery

Identifiers

PMID39957851
PMCPMC11783629

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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.