의료 빅 데이터의 활용과 인간공학적 의미에 대한 문헌연구
= A Review on the Applications of Medical Big Data and Ergonomic Implications
저자[authors] 박희석(Hee Sok Park)
학술지명[periodical name] 大韓人間工學會誌
권호사항[Volume/Issue] Vol.37No.2[2018]
발행처[publisher] 대한인간공학회
자료유형[Document Type] 학술저널
수록면[Pagination] 143-154
언어[language] Korean
발행년[Publication Year] 2018
주제어[descriptor] Big data,Medical,Healthcare,Review
초록[abstracts]
[Objective: This study aims to identify the past and current situations through literature review on how Big Data is utilized in the medical field, and to suggest ergonomic implications and directions of big data technology in the medical field in the future. Background: As the investment on the medical treatment and medical service is expanded and the amount of medical information is increased due to introduction of electronic medical records, utilization of Big Data technology in medical field is increasing. Method: The articles from academic journals, conference proceedings, and professional publications published after year 2000 were searched using such data bases as DBPia. The literature to be studied was searched by keywords of "medical", "health", "healthcare", "big data", "medical data", and their combinations. Results: The parties using medical Big Data were classified into three ones, including the customers or patients using medical services, the medical institutions providing medical services, and the national or public institutions. In addition, we classified personal information problems, which all three parties should consider in common. Conclusion: Customers, medical institutions, national or public institutions can benefit from the use of medical Big Data in making various decisions. It is also necessary to take measures to solve the problem of leakage of personal information by using Medical Big Data. Application: It will be applied to guide the direction of research to safeguard personal information safely while valuing the Big Data that will lead the development of medical field.]
목차[Table of content] 1. Introduction 2. Method 3. Results 4. Conclusion References