전기전자학회논문지 (Journal of IKEEE)

  • 제20권1호
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  • Pages.16-25
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  • 2016
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  • 1226-7244(pISSN)
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  • 2288-243X(eISSN)
한국전기전자학회 (Institute of Korean Electrical and Electronics Engineers)
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분류회귀나무를 이용한 의료서비스 적기처리 예측모형

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

  • 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)
  • 투고 : 2015.12.10
  • 심사 : 2016.01.27
  • 발행 : 2016.03.31
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초록

의학적 진단을 내리기 위해 시행되는 검사의 소요시간(turnaround time, TAT)은 환자대기시간과 직결되며 중요한 의료서비스 평가항목 중 하나이다. 본 연구에서는 주요 영상의학검사를 대상으로 TAT를 측정하고, 그 결과가 의료기관이 설정한 기준치를 달성하는지 여부를 분석하였다. 분류회귀나무 알고리즘을 이용한 예측 결과, "진료과", "상병", "검사종류", "실시월"이 적기처리 달성에 가장 큰 영향을 주는 요인으로 확인되었다. 본 연구는 의료서비스의 적기처리를 예측하는 모형을 통하여 의료서비스 지연을 사전에 조치할 수 있는 수단을 제공하였다는 데에 큰 의미가 있다.

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.

키워드

참고문헌

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피인용 문헌

  1. MR-CART: Multiresponse optimization using a classification and regression tree method vol.33, pp.3, 2021, https://doi.org/10.1080/08982112.2021.1888120