Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Development of Mortality Model of Severity-Adjustment Method of AMI Patients

급성심근경색증 환자 중증도 보정 사망 모형 개발

  • Lim, Ji-Hye (Department of Health & Medical Administration, Dongu College) ;
  • Nam, Mun-Hee (Division of Nursing, Kaya University)
  • 임지혜 (동주대학교 보건의료행정과) ;
  • 남문희 (가야대학교 간호학과)
  • Received : 2012.04.30
  • Accepted : 2012.06.07
  • Published : 2012.06.30
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Abstract

The study was done to provide basic data of medical quality evaluation after developing the comorbidity disease mortality measurement modeled on the severity-adjustment method of AMI. This study analyzed 699,701 cases of Hospital Discharge Injury Data of 2005 and 2008, provided by the Korea Centers for Disease Control and Prevention. We used logistic regression to compare the risk-adjustment model of the Charlson Comorbidity Index with the predictability and compatibility of our severity score model that is newly developed for calibration. The models severity method included age, sex, hospitalization path, PCI presence, CABG, and 12 variables of the comorbidity disease. Predictability of the newly developed severity models, which has statistical C level of 0.796(95%CI=0.771-0.821) is higher than Charlson Comorbidity Index. This proves that there are differences of mortality, prevalence rate by method of mortality model calibration. In the future, this study outcome should be utilized more to achieve an improvement of medical quality evaluation, and also models will be developed that are considered for clinical significance and statistical compatibility.

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.

Keywords

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