Evidence map›Paper›PMID 25247169›Full record

ArticleAnnals of surgical treatment and research2014

Evaluating the efficacy of the current diagnosis-related group reimbursement system for laparoscopic appendectomy at a single institute in Korea.

Ri Na Yoo, Chul-Woon Chung, Jong-Woo Kim

Erratum issuedAbstract read
In one paragraph

Article in Annals of surgical treatment and research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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.

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4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

3 authors.

Ri Na YooDepartment of Surgery, CHA Bundang Medical Center, CHA University, Seongnam, Korea.
Chul-Woon ChungDepartment of Surgery, International St. Mary's Hospital, Incheon, Korea.
Jong-Woo KimDepartment of Surgery, CHA Bundang Medical Center, CHA University, Seongnam, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe diagnosis-related group (DRG) system has been adapted to reduce overall medical costs by grouping and classifying relatively homogenous patients based on similar resource consumption patterns in the treatment. However, despite its wide range of disease manifestation from early inflammation to severe peritonitis, acute appendicitis is included in the DRG system. Responding to a need to assess the DRG system for patients diagnosed with appendicitis, this study evaluates the efficacy of the current DRG system applied to a broad spectrum of the patients with appendicitis undergoing laparoscopic appendectomy.

methodsA retrospective review was conducted of the patients who underwent laparoscopic appendectomy. Based on the DRG codes' classification, the patients were analyzed for the amount of DRG reimbursement and the total in-patient cost in relation to the time sequence of the disease onset. Statistical analysis was performed to find factors correlated with the DRG reimbursement and total in-patient cost.

resultsFindings indicate that, as the symptom duration becomes prolonged, the CRP level and the use of peritoneal drainage increased. Patients with a symptom duration greater than 24 hours required approximately 5 days of hospital stay, 0.5 day longer in the length of hospital stay than that of patients with less than 12 hours of the onset time. As expected, the amount of DRG reimbursement and the total in-patient cost accumulated as the symptom duration increased.

conclusionThe current DRG reimbursement system for the patients undergoing laparoscopic appendectomy recompenses a broad spectrum of patients diagnosed with appendicitis effectively.

Indexed as

AppendectomyDiagnosis-related groupsLaparoscopySeverity of illness index

Identifiers

PMID25247169
PMCPMC4170584

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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.