Journal of Preventive Medicine and Public Health

Systematic Review

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.; Summary

Korean 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.

Original Article

Trends in the Quality of Primary Care and Acute Care in Korea From 2008 to 2020: A Cross-sectional Study: Yeong Geun Gwon, Seung Jin Han, Kyoung Hoon Kim; J Prev Med Public Health. 2023;56(3):248-254. Published online April 12, 2023; DOI: https://doi.org/10.3961/jpmph.23.015

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Abstract Summary PDF: Objectives
Measuring the quality of care is paramount to inform policies for healthcare services. Nevertheless, little is known about the quality of primary care and acute care provided in Korea. This study investigated trends in the quality of primary care and acute care.
Methods
Case-fatality rates and avoidable hospitalization rates were used as performance indicators to assess the quality of primary care and acute care. Admission data for the period 2008 to 2020 were extracted from the National Health Insurance Claims Database. Case-fatality rates and avoidable hospitalization rates were standardized by age and sex to adjust for patients’ characteristics over time, and significant changes in the rates were identified by joinpoint regression.
Results
The average annual percent change in age-/sex-standardized case-fatality rates for acute myocardial infarction was -2.3% (95% confidence interval, -4.6 to 0.0). For hemorrhagic and ischemic stroke, the age-/sex-standardized case-fatality rates were 21.8% and 5.9%, respectively in 2020; these rates decreased since 2008 (27.1 and 8.7%, respectively). The average annual percent change in age-/sex-standardized avoidable hospitalization rates ranged from -9.4% to -3.0%, with statistically significant changes between 2008 and 2020. In 2020, the avoidable hospitalization rates decreased considerably compared with the 2019 rate because of the coronavirus disease 2019 pandemic.
Conclusions
The avoidable hospitalization rates and case-fatality rates decreased overall during the past decade, but they were relatively high compared with other countries. Strengthening primary care is an essential requirement to improve patient health outcomes in the rapidly aging Korean population.; Summary

Korean summary
본 연구에서는 급성심근경색증과 뇌졸중 치명률, 외래진료 민감질환의 예방 가능한 입원율을 사용하여 한국의 의료 질 수준을 분석하였다. 2008~2020년 동안 치명률과 예방 가능한 입원율은 감소하는 추세이다. 그러나, 예방 가능한 입원율은 다른 국가에 비해 상대적으로 높아 환자의 건강결과 향상을 위하여 일차의료 강화가 요구된다.

English Abstracts

Impact of Health Insurance Type on the Quality of Hemodialysis Services: A Multilevel Analysis.: Jin Hee Jung, Soon Man Kwon, Kyoung Hoon Kim, Seon Kyoung Lee, Dong Sook Kim; J Prev Med Public Health. 2010;43(3):245-256.; DOI: https://doi.org/10.3961/jpmph.2010.43.3.245

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Abstract PDF

OBJECTIVES
This study aims to compare quality indicators for the hemodialysis services between patients with health insurance and those with medical aid. METHODS: This study used data from sampled hospitals that provided a hemodialysis service. A total of 2287 patients were selected, and the information for hemodialysis service has been granted from medical record reviews. A multi-level regression analysis was used to examine the differences in process and outcome indicators for hemodialysis between patients with health insurance and those with medical aid. Process indicators were defined as: frequency of hemodialysis, hemodialysis time, erythropoietin (EPO) use, measurement of hemodialysis dose at least once a month, measurement of phosphate at least once every three months, and measurement of albumin at least once every three months. Outcome indicators were defined as: hemodialysis adequacy, anemia management, blood pressure management, and calcium, phosphate and nutrition management. The total scores for outcome indicators ranged from 0 (worst) to 4 (best). RESULTS: There was a significant difference in the measurement of hemodialysis dose at least once a month between patients with health insurance and those with medical aid (OR 0.66, 95% CI=0.43-0.99). However, frequency of hemodialysis, hemodialysis time, EPO use, measurement of phosphate at least once every three months, measurement of albumin at least once every three months, hemodialysis adequacy management, Hb> or =11 g/dL, blood pressure within the range of 100-140/60-90 mmHg, calcium x phosphate< or =55 g2/dL2 and albumin> or =4 g/dL were not significantly different between the groups. CONCLUSIONS: There were no significant differences in outcome indicators for hemodialysis between the groups. Further studies are warranted into the mechanism that results in no differences in the outcome indicators for hemodialysis.

Summary

Citations

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Association Between Prophylactic Antibiotic Use and Surgical Site Infection Based on Quality Assessment Data in Korea.: Kyoung Hoon Kim, Choon Seon Park, Jin Hee Chang, Nam Soon Kim, Jin Seo Lee, Bo Ram Choi, Byung Ran Lee, Kyoo Duck Lee, Sun Min Kim, Seon A Yeom; J Prev Med Public Health. 2010;43(3):235-244.; DOI: https://doi.org/10.3961/jpmph.2010.43.3.235

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Abstract PDF

OBJECTIVES
To examine the prophylactic antibiotic use in reducing surgical site infection. METHODS: This was a retrospective study for patients aged 18 years and older who underwent gastrectomy, cholecystectomy, colectomy, cesarean section and hysterectomy. The data source was quality assessment data of the Health Insurance Review & Assessment Service gathered from medical records of 302 national hospitals. Prophylactic antibiotic use was defined as: timely antibiotic administration or inappropriate antibiotic selection. We performed hierarchical logistic regression to examine the association between prophylactic antibiotic use and surgical site infection with adjustment for covariates. RESULTS: The study population consisted of 16 348 patients (1588 gastrectomies, 2327 cholecystectomies, 1,384 colectomies, 3977 hysterectomies and 7072 cesarean sections) and surgical site infection was identified in 351 (2.1%) patients. The rates of timely antibiotic administration and inappropriate antibiotic selection varied according to procedures. Cholecystectomy patients who received timely prophylactic antibiotic had a significantly reduced risk of surgical site infection compared with those who did not receive a timely prophylactic antibiotics (OR 0.64, 95% CI=0.50-0.83), but no significant reduction was observed for other procedures. When inappropriate prophylactic antibiotics were given, the risk of surgical site infection significantly increased: 8.26-fold (95% CI=4.34-15.7) for gastrectomy, 4.73-fold (95% CI=2.09-10.7) for colectomy, 2.34-fold (95% CI=1.14-4.80) for cesarean section, 4.03-fold (95% CI=1.93-8.42) for hysterectomy. CONCLUSIONS: This study examines the association among timely antibiotic administration, inappropriate antibiotic selection and surgical site infection. Patients who received timely and appropriate antibiotics had a decreased risk of surgical site infection. Efforts to improve the timing of antibiotic administration and use of appropriate antibiotic are needed to lower the risk of surgical site infection.

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Comparative Study on Three Algorithms of the ICD-10 Charlson Comorbidity Index with Myocardial Infarction Patients.: Kyoung Hoon Kim; J Prev Med Public Health. 2010;43(1):42-49.; DOI: https://doi.org/10.3961/jpmph.2010.43.1.42

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Abstract PDF

OBJECTIVES
To compare the performance of three International Statistical Classification of Diseases, 10th Revision translations of the Charlson comorbidities when predicting in-hospital among patients with myocardial infarction (MI). METHODS: MI patients > or =20 years of age with the first admission during 2006 were identified(n=20,280). Charlson comorbidities were drawn from Heath Insurance Claims Data managed by Health Insurance Review and Assessment Service in Korea. Comparisions for various conditions included (a) three algorithms (Halfon, Sundararajan, and Quan algorithms), (b) lookback periods (1-, 3- and 5-years), (c) data range (admission data, admission and ambulatory data), and (d) diagnosis range (primary diagnosis and first secondary diagnoses, all diagnoses). The performance of each procedure was measured with the c-statistic derived from multiple logistic regression adjusted for age, sex, admission type and Charlson comorbidity index. A bootstrapping procedure was done to determine the approximate 95% confidence interval. RESULTS: Among the 20,280 patients, the mean age was 63.3 years, 67.8% were men and 7.1% died while hospitalized. The Quan and Sundararajan algorithms produced higher prevalences than the Halfon algorithm. The c-statistic of the Quan algorithm was slightly higher, but not significantly different, than that of other two algorithms under all conditions. There was no evidence that on longer lookback periods, additional data, and diagnoses improved the predictive ability. CONCLUSIONS: In health services study of MI patients using Health Insurance Claims Data, the present results suggest that the Quan Algorithm using a 1-year lookback involving primary diagnosis and the first secondary diagnosis is adequate in predicting in-hospital mortality.

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A Comparative Study on Comorbidity Measurements with Lookback Period using Health Insurance Database: Focused on Patients Who Underwent Percutaneous Coronary Intervention.: Kyoung Hoon Kim, Lee Su Ahn; J Prev Med Public Health. 2009;42(4):267-273.; DOI: https://doi.org/10.3961/jpmph.2009.42.4.267

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Abstract PDF

OBJECTIVES
To compare the performance of three comorbidity measurements (Charlson comorbidity index, Elixhauser's comorbidity and comorbidity selection) with the effect of different comorbidity lookback periods when predicting in-hospital mortality for patients who underwent percutaneous coronary intervention. METHODS: This was a retrospective study on patients aged 40 years and older who underwent percutaneous coronary intervention. To distinguish comorbidity from complications, the records of diagnosis were drawn from the National Health Insurance Database excluding diagnosis that admitted to the hospital. C-statistic values were used as measures for in comparing the predictability of comorbidity measures with lookback period, and a bootstrapping procedure with 1,000 replications was done to determine approximate 95% confidence interval. RESULTS: Of the 61,815 patients included in this study, the mean age was 63.3 years (standard deviation: +/-10.2) and 64.8% of the population was male. Among them, 1,598 (2.6%) had died in hospital. While the predictive ability of the Elixhauser s comorbidity and comorbidity selection was better than that of the Charlson comorbidity index, there was no significant difference among the three comorbidity measurements. Although the prevalence of comorbidity increased in 3 years of lookback periods, there was no significant improvement compared to 1 year of a lookback period. CONCLUSIONS: In a health outcome study for patients who underwent percutaneous coronary intervention using National Health Insurance Database, the Charlson comorbidity index was easy to apply without significant difference in predictability compared to the other methods. The one year of observation period was adequate to adjust the comorbidity. Further work to select adequate comorbidity measurements and lookback periods on other diseases and procedures are needed.

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Development and validation of comorbidity index in South Korea
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Prognostic Impact of Charlson Comorbidity Index Obtained from Medical Records and Claims Data on 1-year Mortality and Length of Stay in Gastric Cancer Patients.: Min Ho Kyung, Seok Jun Yoon, Hyeong Sik Ahn, Se min Hwang, Hyun Ju Seo, Kyoung Hoon Kim, Hyeung Keun Park; J Prev Med Public Health. 2009;42(2):117-122.; DOI: https://doi.org/10.3961/jpmph.2009.42.2.117

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Abstract PDF

OBJECTIVES
We tried to evaluate the agreement of the Charlson comorbidity index values (CCI) obtained from different sources (medical records and National Health Insurance claims data) for gastric cancer patients. We also attempted to assess the prognostic value of these data for predicting 1-year mortality and length of the hospital stay (length of stay). METHODS: Medical records of 284 gastric cancer patients were reviewed, and their National Health Insurance claims data and death certificates were also investigated. To evaluate agreement, the kappa coefficient was tested. Multiple logistic regression analysis and multiple linear regression analysis were performed to evaluate and compare the prognostic power for predicting 1 year mortality and length of stay. RESULTS: The CCI values for each comorbid condition obtained from 2 different data sources appeared to poorly agree (kappa: 0.00-0.59). It was appeared that the CCI values based on both sources were not valid prognostic indicators of 1-year mortality. Only medical record-based CCI was a valid prognostic indicator of length of stay, even after adjustment of covariables (beta = 0.112, 95% CI = [0.017-1.267]). CONCLUSIONS: There was a discrepancy between the data sources with regard to the value of CCI both for the prognostic power and its direction. Therefore, assuming that medical records are the gold standard for the source for CCI measurement, claims data is not an appropriate source for determining the CCI, at least for gastric cancer.

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