• 보건행정학회지
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• 제21권4호
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• pp.541-564
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• 2011

This study aimed to investigate health outcome of acute myocardial infarction (AMI) patients such as mortality and length of stay in hospital and to identify factors associated with the health outcome according to the comorbidity index. Nation-wide representative samples of 3,748 adult inpatients aged between 20-85 years with acute myocardial infarction were derived from the Korea National Hospital Discharge Injury Survey, 2005-2008. Comorbidity index was measured using the Charlson Comorbidity Index (CCI). The data were analyzed using t-test, ANOVA, multiple regression, logistic regression analysis in order to investigate the effect of comorbidity on health outcome. According to the study results, the factors associated with length of hospital stay of acute myocardial infarction patients were gender, insurance type, residential area scale, admission route, PCI perform, CABG perform, and CCI. The factors associated with mortality of acute myocardial infarction patients were age, admission route, PCI perform, and CCI. CCI with a higher length of hospital stay and mortality also increased significantly. This study demonstrated comorbidity risk adjustment for health outcome and presented important data for health care policy. In the future study, more detailed and adequate comorbidity measurement tool should be developed, so patients' severity can be adjusted accurately.

• Journal of Preventive Medicine and Public Health
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• 제42권4호
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• pp.267-273
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• 2009

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: ${\pm}$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.

• 한국병원경영학회지
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• 제14권1호
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• pp.23-35
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• 2009

The objectives of the present study is to examine the validity of Charlson Comorbidity Index(CCI) based on medical record data; to utilize the index to determine outcome indexes such as mortality, length of stay and cost for the domestic patients whose have received total hip arthroplasty. Based on medical record date, 1-year Mortality was analyzed to be 0.664 of C statistic. The $R^2$ for the predictability for length of stay and the cost was about 0.0181, 0.1842. Fee of national health insurance and total cost including the cost not covered by insurance, also had statistically significance above 3 points of Charlson point score(p=0.0290, 0.0472; $p.{\le}0.05$). The 1-year mortality index, length of stay and cost of the total hip arthroplasty patients which was obtained utilizing CCI have a limitative prediction power and therefore should be carefully analyzed for use.

• 한국콘텐츠학회논문지
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• 제16권3호
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• pp.22-32
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• 2016

인구구조의 급속한 고령화로 뇌졸중 질환의 발생빈도와 진료비가 지속적으로 증가하고 있다. 이에 본 연구는 대표성이 있는 퇴원손상심층조사 자료를 이용하여 뇌졸중 환자의 Charlson comorbidity index에 따른 사망률 현황을 살펴보고, 뇌졸중 환자의 사망에 영향을 미치는 요인을 분석해 보고자 시행하였다. 2005년에서 2010년까지의 6년간 퇴원손상심층조사 자료를 이용하였으며, 연령이 20세 이상이며 주진단명이 뇌졸중으로 분류된 21,494건을 대상으로 분석하였다. 분석대상자의 동반상병 분포와 CCI에 따른 사망률 현황을 파악하기 위해 기술통계를 실시하였으며, 뇌졸중 환자의 사망에 영향을 미치는 요인을 파악하기 위해서는 로지스틱 회귀분석 기법을 이용하였다. 분석 결과, 뇌졸중 환자의 사망에 유의한 영향을 미치는 독립변수는 연령, 보험유형, 거주지 도시규모, 병상규모, 의료기관 소재지, 입원경로, Physical therapy 유무, 뇌수술 시행 유무, 뇌졸중 유형, CCI로 나타났다. 이는 뇌졸중 환자의 연령, 뇌졸중 유형, 동반상병의 위험요인에 따른 좀 더 효율적인 접근법과 모니터링이 필요하며, 의료급여 환자의 지원 확대가 개선되어야 함을 시사해준다. 이러한 결과들은 향후 뇌졸중 환자들의 의료의 질 평가와 보건의료 정책 수립에 기초자료로 의미 있게 활용되어질 수 있으리라 여겨진다.

• Journal of Preventive Medicine and Public Health
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• 제43권1호
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• pp.42-49
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• 2010

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 ${\geq}20$ 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.

• 한국산학기술학회논문지
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• 제13권6호
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• pp.2672-2679
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• 2012

본 연구는 급성심근경색증 환자의 사망률 측정을 위한 중증도 보정 모형을 개발하여 의료의 질 평가에 필요한 기초자료를 제공하고자 수행되었다. 이를 위해서 질병관리본부의 2005-2008년 퇴원손상환자 699,701건의 자료를 분석하였다. Charlson Comorbidity Index 보정 방법을 이용한 경우와 새롭게 개발된 중증도 보정 모형의 예측력 및 적합도를 비교하기 위해 로지스틱 회귀분석을 실시하였다. 새롭게 개발된 모형에는 연령, 성, 입원경로, PCI 유무, CABG 유무, 동반질환 12가지 변수가 포함되었다. 분석결과 CCI를 이용한 중증도 보정 모형보다 새롭게 개발된 중증도 보정 사망 모형의 C 통계량 값이 0.796(95%CI=0.771-0.821)으로 더 높아 모형의 예측력이 더 우수한 것으로 나타났다. 본 연구를 통하여 중증도 보정 방법에 따라 사망률, 유병률, 예측력에도 차이가 있음을 확인하였다. 향후에 이모형은 의료의 질 평가에 이용하고, 질환별로 임상적 의미와 특성, 모형의 통계적 적합성 등을 고려한 중증도 보정모형이 계속해서 개발되어야 할 것이다.

• 보건행정학회지
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• 제19권4호
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• pp.18-32
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• 2009

The goal of this study was to predict the health outcomes of lung cancer surgery based on the Charlson comorbidity index (CCI). An attempt was likewise made to assess the prognostic value of such data for predicting mortality, survival rate, and length of hospital stay. A medical-record review of 389 patients with non-small-cell lung cancer was performed. To evaluate the agreement, the kappa coefficient was tested. Logistic-regression analysis was also conducted within two years after the surgery to determine the association of CCI with death. Survival and multiple-regression analyses were used to evaluate the relationship between CCI and the hospital care outcomes within two-year survival after lung cancer surgery and the length of hospital stay. The results of the study showed that CCI is a valid prognostic indicator of two-year mortality and length of hospital stay, and that it shows the health outcomes, such as death, survival rate, and length of hospital stay, after the surgery, thus enabling the development and application of the methodology using a systematic and objective scale for the results.

• 보건행정학회지
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• 제26권1호
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• pp.71-78
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• 2016

The value of using health insurance claim database is continuously rising in healthcare research. In studies where comorbidities act as a confounder, comorbidity adjustment holds importance. Yet researchers are faced with a myriad of options without sufficient information on how to appropriately adjust comorbidity. The purpose of this study is to assist in selecting an appropriate index, look back period, and data range for comorbidity adjustment. No consensus has been formed regarding the appropriate index, look back period and data range in comorbidity adjustment. This study recommends the Charlson comorbidity index be selected when predicting the outcome such as mortality, and the Elixhauser's comorbidity measures be selected when analyzing the relations between various comorbidities and outcomes. A longer look back period and inclusion of all diagnoses of both inpatient and outpatient data led to increased prevalence of comorbidities, but contributed little to model performance. Limited data range, such as the inclusion of primary diagnoses only, may complement limitations of the health insurance claim database, but could miss important comorbidities. This study suggests that all diagnoses of both inpatients and outpatients data, excluding rule-out diagnosis, be observed for at least 1 year look back period prior to the index date. The comorbidity index, look back period, and data range must be considered for comorbidity adjustment. To provide better guidance to researchers, follow-up studies should be conducted using the three factors based on specific diseases and surgeries.

• Journal of Preventive Medicine and Public Health
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• 제42권2호
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• pp.117-122
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• 2009

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.

• Journal of Periodontal and Implant Science
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• 제48권2호
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• pp.92-102
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• 2018

Purpose: This study investigated the validity of the Charlson comorbidity index (CCI) as a predictor of periodontal disease (PD) over a 12-year period. Methods: Nationwide representative samples of 149,785 adults aged ${\geq}60$ years with PD (International Classification of Disease, 10th revision [ICD-10], K052-K056) were derived from the National Health Insurance Service-Elderly Cohort during 2002-2013. The degree of comorbidity was measured using the CCI (grade 0-6), including 17 diseases weighted on the basis of their association with mortality, and data were analyzed using multivariate Cox proportional-hazards regression in order to investigate the associations of comorbid diseases (CDs) with PD. Results: The multivariate Cox regression analysis with adjustment for sociodemographic factors (sex, age, household income, insurance status, residence area, and health status) and CDs (acute myocardial infarction, congestive heart failure, peripheral vascular disease, cerebral vascular accident, dementia, pulmonary disease, connective tissue disorders, peptic ulcer, liver disease, diabetes, diabetes complications, paraplegia, renal disease, cancer, metastatic cancer, severe liver disease, and human immunodeficiency virus [HIV]) showed that the CCI in elderly comorbid participants was significantly and positively correlated with the presence of PD (grade 1: hazard ratio [HR], 1.11; P<0.001; grade ${\geq}2$: HR, 1.12, P<0.001). Conclusions: We demonstrated that a higher CCI was a significant predictor of greater risk for PD in the South Korean elderly population.