Big Data Analysis: Medical Accident

Abstract

Background/Objectives: Medical accidents have been happening in major large hospitals and real-time search queries for portal sites are increasing. We purpose to provide basic data on medical dispute resolution and medical accident prevention.
Method/Statistical Analysis: We based data collected through educational and academic information sources(RISS) and *aver search as big data, and analyzed the keywords and the network analyzed by the ‘Medical accident’ keyword. The frequency, ranking, and connection of the keywords were analyzed through the process of processing the collected unstructured text into the data suitable for research and analysis.
Findings: As a result, in case of the academic research related to the medical accidents, the study on the medical dispute is most active. In the analysis of the network, the medical accidents lead to the medical disputes and are mostly resolved by law in a manner that judge criminal responsibility and other responsibilities(punishment and compensation).Analysis of search words from news, blogs and Internet cafes, and the most frequently mentioned keyword related to medical accidents was criminal responsibility. In the analysis of the network it will be as follows: the handling of medical accidents involving criminal liability and other liabilities shall result in punitive damages resulting from legal proceedings or monetary damages resulting from civil agreements.
Improvements/Applications: We suggest that the human, institutional, and physical environment should be improved to avoid medical accidents, conflicts and litigation.