Mining Doctor Shopping Behavior from NHIR Databases

碩士 === 世新大學 === 資訊管理學研究所(含碩專班) === 98 === In recent years, cancer diseases threat people’s lives and the proportion of people with cancer has been rising gradually year by year. We get some information from the Health department announced:「cancer has been ranked among the top ten causes of death in...

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Bibliographic Details
Main Authors: Wen-hui Lee, 李玟慧
Other Authors: none
Format: Others
Language:zh-TW
Published: 2010
Online Access:http://ndltd.ncl.edu.tw/handle/23294231708181770523
Description
Summary:碩士 === 世新大學 === 資訊管理學研究所(含碩專班) === 98 === In recent years, cancer diseases threat people’s lives and the proportion of people with cancer has been rising gradually year by year. We get some information from the Health department announced:「cancer has been ranked among the top ten causes of death in the first from 1982 to 2009」. If this trend remains unchanged, expect the future of cancer will continue to be one of the greatest threat to the health of citizens. In this study, we propose a framework to mine useful information from medical records kept by National Health Insurance Research Database in Taiwan from 2003 to 2008. We used data mining technology association rules and sequential pattern analysis to provide cancer patients and their families in the choice of medical treatment information is available. The main results of our study included: (1) Finding candidate hospitals for a certain cancer, (2) Finding the time sequence associations among candidate hospitals, and (3) Analyzing the results of doctor shopping for cancer diseases. Results from this Study that we know the top three cancer - lung cancer, liver cancer, colon cancer in 2009. The North & Central District of patients have preferred counseling, attendance, significant treatment in the same medical place. The patients with central District will go to a Western merge hospital and Chinese medicine clinics. The Southern District of cancer patients undergoing major treatment, there will be second opinion of behavior from different hospitals. In addition, Taitung & Hualien & Penghu & Kinmen County in Taiwan of patients are the same situation.