Evidence map›Paper›PMID 38013409›Full record

ReviewJournal of preventive medicine and public health = Yebang Uihakhoe chi2024

Adjusting for Confounders in Outcome Studies Using the Korea National Health Insurance Claim Database: A Review of Methods and Applications.

Seung Jin Han, Kyoung Hoon Kim

Abstract readReview
In one paragraph

Review in Journal of preventive medicine and public health = Yebang Uihakhoe chi, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Reporting Quality for Comorbidity Adjustment in Studies Using Korean Health Insurance Claim Data: A Scoping Review.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Trends in Regional Disparities in Cardiovascular Surgery and Mortality in Korea: A National Cross-sectional Study.Journal of preventive medicine and public health = Yebang Uihakhoe chi · 2024
    Article
  9. Article
  10. 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

2 authors.

Seung Jin HanReview and Assessment Research Institute, Health Insurance Review & Assessment Service, Wonju, Korea.
Kyoung Hoon KimInternational Policy Research Division, Health Insurance Review & Assessment Service, Wonju, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAdjusting for potential confounders is crucial for producing valuable evidence in outcome studies. Although numerous studies have been published using the Korea National Health Insurance Claim Database, no study has critically reviewed the methods used to adjust for confounders. This study aimed to review these studies and suggest methods and applications to adjust for confounders.

methodsWe conducted a literature search of electronic databases, including PubMed and Embase, from January 1, 2021 to December 31, 2022. In total, 278 studies were retrieved. Eligibility criteria were published in English and outcome studies. A literature search and article screening were independently performed by 2 authors and finally, 173 of 278 studies were included.

resultsThirty-nine studies used matching at the study design stage, and 171 adjusted for confounders using regression analysis or propensity scores at the analysis stage. Of these, 125 conducted regression analyses based on the study questions. Propensity score matching was the most common method involving propensity scores. A total of 171 studies included age and/or sex as confounders. Comorbidities and healthcare utilization, including medications and procedures, were used as confounders in 146 and 82 studies, respectively.

conclusionsThis is the first review to address the methods and applications used to adjust for confounders in recently published studies. Our results indicate that all studies adjusted for confounders with appropriate study designs and statistical methodologies; however, a thorough understanding and careful application of confounding variables are required to avoid erroneous results.

Indexed as

Databases, FactualNational Health ProgramsPropensity ScoreConfounding Factors, EpidemiologicHumansInsurance Claim ReviewOutcome Assessment, Health CareRegression AnalysisRepublic of KoreaConfounderHealth Insurance Claim DatabaseRisk adjustmentStatistical methodology

Identifiers

PMID38013409
PMCPMC10861329

What OpenQuestion holds

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LicenceCC BY-NC
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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.