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- 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
- J Prev Med Public Health. 2024;57(1):1-7. Published online November 16, 2023
- DOI: https://doi.org/10.3961/jpmph.23.250
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Abstract
Summary
PDF - Objectives
Adjusting 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.
Methods
We 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.
Results
Thirty-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.
Conclusions
This 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. -
SummaryKorean summary
건강보험청구자료를 사용한 성과연구에서는 교란요인 통제가 중요하다. 최근 발표된 연구들은 연구설계와 통계 분석 과정에 적절하게 교란요인을 통제하였다. 연구의 질을 높이기 위해서는 건강보험청구자료에서 수집 가능한 교란 요인에 대한 이해와 방법론적 가이드라인이 요구된다.Key Message
All recently published studies using Health Insurance Claims Database adjusted for confounders with appropriate study designs and statistical methodologies. The review suggests the need for careful application of confounding variables and the methodological guidance to improve the quality of outcome studies.
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