Earticle

초록

영어

This research paper introduces the application and implementation of medical decision metrics that classifies medical decision-making into four different metrics using statistical diagnostic tools, such as confusion matrix, normal distribution, Bayesian prediction and Receiver Operating Curve(ROC). In this study, the metrics are developed based on cross-section study, cohort study and case-control study done by systematic literature review and reformulated the structure of type Ⅰ error, type Ⅱ error, confidence level and power of detection. The study proposed implementation strategies for 10 quality improvement activities via 14 medical decision metrics which consider specificity and sensitivity in terms of  and  . Examples of ROC implication are depicted in this paper with a useful guidelines to implement a continuous quality improvement, not only in a variable acceptance sampling in Quality Control(QC) but also in a supplier grading score chart in Supplier Chain Management(SCM) quality. This research paper is the first to apply and implement medical decision-making tools as quality improvement activities. These proposed models will help quality practitioners to enhance the process and product quality level.

목차

Abstract
 1. 서론
 2. 의학적 의사결정 지표의 고찰 및 해석
  2.1 Confusion Matrix에 의한 이해
  2.2 정규확률분포에 의한 이해
  2.3 ROC에 의한 이해
  2.4 Bayes 이론에 의한 이해
  2.5 의학적 지표를 이용한 통계기법의 해석
 3. 품질통계에서 ROC 적용방안
 4. 결론
 5. 참고문헌

키워드

저자

• 최성운 [ Sungwoon Choi | 가천대학교 산업공학과 ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  대한안전경영과학회지 [Journal of Korea Safety Management & Science]

• 간기

  계간

• pISSN

  1229-6783

• eISSN

  2288-1484

• 수록기간

  1999~2025

• 십진분류

  KDC 530 DDC 620