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A Prediction Model of Timely Processing on Medical Service using Classification and Regression Tree

분류회귀나무를 이용한 의료서비스 적기처리 예측모형

  • Lee, Jong-Chan (Dept. of Industrial and Information Systems, Seoul National University of Science and Technology) ;
  • Jeong, Seung-Woo (The Catholic University of Korea. Uijeongbu St.Mary Hospital) ;
  • Lee, Won-Young (Dept. of Industrial and Information Systems, Seoul National University of Science and Technology)
  • Received : 2015.12.10
  • Accepted : 2016.01.27
  • Published : 2016.03.31

Abstract

Turnaround time (called, TAT) for imaging test, which is necessary for making a medical diagnosis, is directly related to the patient's waiting time and it is one of the important performance criteria for medical services. In this paper, we measured the TAT from major imaging tests to see it met the reference point set by the medical institutions. Prediction results from the algorithm of classification regression tree (called, CART) showed "clinics", "diagnosis", "modality", "test month" were identified as main factors for timely processing. This study had a contribution in providing means of prevention of the delay on medical services in advance.

Acknowledgement

Supported by : Seoul National University of Science and Technology

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