Journal of Preventive Medicine and Public Health

The Korean Society for Preventive Medicine (대한예방의학회)
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Does a Higher Coronary Artery Bypass Graft Surgery Volume Always have a Low In-hospital Mortality Rate in Korea?

관상동맥우회로술 환자의 위험도에 따른 수술량과 병원내 사망의 관련성

  • Lee, Kwang-Soo (Department of Hospital Management, College of Medicine, Eulji University) ;
  • Lee, Sang-Il (Department of Preventive Medicine, College of Medicine, University of UIsan)
  • 이광수 (을지의과대학교 병원경영학과) ;
  • 이상일 (울산대학교 의과대학 예방의학교실)
  • Published : 2006.01.31
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Abstract

Objectives: To propose a risk-adjustment model with using insurance claims data and to analyze whether or not the outcomes of non-emergent and isolated coronary artery bypass graft surgery (CABG) differed between the low- and high-volume hospitals for the patients who are at different levels of surgical risk. Methods: This is a cross-sectional study that used the 2002 data of the national health insurance claims. The study data set included the patient level data as well as all the ICD-10 diagnosis and procedure codes that were recorded in the claims. The patient's biological, admission and comorbidity information were used in the risk-adjustment model. The risk factors were adjusted with the logistic regression model. The subjects were classified into five groups based on the predicted surgical risk: minimal (<0.5%), low (0.5% to 2%), moderate (2% to 5%), high (5% to 20%), and severe (=20%). The differences between the low- and high-volume hospitals were assessed in each of the five risk groups. Results: The final risk-adjustment model consisted of ten risk factors and these factors were found to have statistically significant effects on patient mortality. The C-statistic (0.83) and Hosmer-Lemeshow test ($x^2=6.92$, p=0.55) showed that the model's performance was good. A total of 30 low-volume hospitals (971 patients) and 4 high-volume hospitals (1,087 patients) were identified. Significant differences for the in-hospital mortality were found between the low- and high-volume hospitals for the high (21.6% vs. 7.2%, p=0.00) and severe (44.4% vs. 11.8%, p=0.00) risk patient groups. Conclusions: Good model performance showed that insurance claims data can be used for comparing hospital mortality after adjusting for the patients' risk. Negative correlation was existed between surgery volume and in-hospital mortality. However, only patients in high and severe risk groups had such a relationship.

Keywords

References

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