運用決策樹技術探討急診病患醫療費用之消耗

Utilization of a Decision Tree for High Expenditure Patients in the Emergency Department

周歆凱(Hsin-Kai Chou) ； 蘇喜(Syi Su) ； 黃興進(Hsin-Ginn Hwang) ； 蔡明足(Ming-Tsu Tsai) ； 翁林仲(Lin-Chung Woung)

《台灣公共衛生雜誌》 25卷6期 (2006/12) Pp. 430-439

https://doi.org/10.6288/TJPH2006-25-06-03

摘要

目標：傳統上，決策樹之分類技術在市場上多運用於顧客資料的區隔分析。然而，本研究也應用該工具來探討急診病患醫療費用之耗用，期望從大量之費用資料庫中，探勘出病患屬性與其醫療費用消耗之潛在關係。方法：本研究收集某醫學中心急診室一年之病患就診資料，並利用資料探勘技術中之決策樹工具來觀察各醫療費用群（低費用組、一般費用組、高費用組）間之病患特質（人口學特質、就醫屬性）的分類；藉由分類規則的建立，可預測病人於就診時可能消耗之醫療費用多寡。結果：決策樹以多層次之樹枝分佈及顏色區塊等視覺化方式呈現研究結果；其中資訊增益順序為（滯留時間＞疾病分類＞離院後動向＞檢傷分級＞科別），該資訊增益之順序也代表屬性影響醫療費用分佈之程度，意即滯留時間為決定急診病色醫療費用多寡之首要因素。結論：本研究建議個案醫院能針對不同類型之病人，給予個人化的照護服務，期望改善病人再回診的情形、降低滯留急診的時間，同時也能降低病人於急診發生之醫療費用。

關鍵字

急診醫學 ； 資料探勘 ； 決策樹

並列摘要

Objective: Traditionally, classification via a decision tree has been primarily used to distinguish between types of customers. In the current study, however, a decision tree was used to track a patient's medical expenditures in the emergency department and determine the potential relationship between patient attributes and expenses, as derived from a large database maintained in the emergency department of the hospital. Method: Patient records were collected inform the emergency department of a medical center over the course of approximately one year and a decision tree was used to classify patient data based on the magnitude of medical expenses incurred (i.e., lower, average, or higher); in the future, we will be able to predict the potential medical expenditures of emergency department patients according to such a classification. Result: The decision tree consisted of multiple levels of branches and color blocks to present the output and the sequence of information gathered (e.g., length of stay＞disease classification＞mode of departure from the hospital＞triage＞medical specific) and reflected the degree to which the distribution of medical expenses were influenced. Conclusion: This research suggests that the hospital can supply professional and personal services to various patients who have some special needs; at the same time, the hospital also can reduce the number of patients that re-visit the emergency department within 72 hours or remain in the emergency department ＞24 hours, thereby decreasing the expenditures within the emergency department.

並列關鍵字

Emergency Medicine ； Data Mining ； Decision Tree

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