Journal of Preventive Medicine and Public Health

The Korean Society for Preventive Medicine (대한예방의학회)
권호 표지

Impact of Risk Adjustment with Insurance Claims Data on Cesarean Delivery Rates of Healthcare Organizations in Korea

건강보험 청구명세서 자료를 이용한 제왕절개 분만율 위험도 보정의 효과

  • Lee, Sang-Il (Department of Preventive Medicine, College of Medicine, University of Ulsan) ;
  • Seo, Kyung (Department of Obstetrics and Gynecology, College of Medicine, Yonsei University) ;
  • Do, Young-Mi (Health Insurance Review Agency) ;
  • Lee, Kwang-Soo (Department of Hospital Management, College of Medicine, Eulji University)
  • 이상일 (울산대학교 의과대학 예방의학교실) ;
  • 서경 (연세대학교 의과대학 산부인과교실) ;
  • 도영미 (건강보험심사평가원 평가실) ;
  • 이광수 (을지의과대학교 병원경영학과)
  • Published : 2005.06.01
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Abstract

Objectives: To propose a risk-adjustment model from insurance claims data, and analyze the changes in cesarean section rates of healthcare organizations after adjusting for risk distribution. Methods: The study sample included delivery claims data from January to September, 2003. A risk-adjustment model was built using the 1st quarter data, and the 2nd and 3rd quarter data were used for a validation test. Patients' risk factors were adjusted using a logistic regression analysis. The c-statistic and Hosmer-Lemeshow test were used to evaluate the performance of the risk-adjustment model. Crude, predicted and risk-adjusted rates were calculated, and compared to analyze the effects of the adjustment. Results: Nine risk factors (malpresentation, eclampsia, malignancy, multiple pregnancies, problems in the placenta, previous Cesarean section, older mothers, bleeding and diabetes) were included in the final risk-adjustment model, and were found to have statistically significant effects on the mode of delivery. The c-statistic (0.78) and Hosmer-Lemeshow test ($x^2$=0.60, p=0.439) indicated a good model performance. After applying the 2nd and 3rd quarter data to the model, there were no differences in the c-statistic and Hosmer-Lemeshow $x^2$. Also, risk factor adjustment led to changes in the ranking of hospital Cesarean section rates, especially in tertiary and general hospitals. Conclusion: This study showed a model performance, using medical record abstracted data, was comparable to the results of previous studies. Insurance claims data can be used for identifying areas where risk factors should be adjusted. The changes in the ranking of hospital Cesarean section rates implied that crude rates can mislead people and therefore, the risk should be adjusted before the rates are released to the public. The proposed risk-adjustment model can be applied for the fair comparisons of the rates between hospitals.

Keywords

References

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