Towards a novel Data Mining System for Medication Error Management

被引:0
|
作者
Touati, Hanae [1 ]
Thabet, Rafika [1 ,2 ]
Fontanili, Franck [1 ]
Cleostrate, Marie-Helene [3 ]
Cufi, Marie-Noelle [3 ]
Lamine, Elyes [4 ,5 ]
机构
[1] Toulouse Univ, CGI, IMT Mines Albi, Albi, France
[2] Sousse Univ, ISITCom, MARS Lab, LR17RS05, Tunis, Tunisia
[3] Intercommunal Hosp Ctr, Castres, France
[4] Toulouse Univ, ISIS Engn, INUC, Castres, France
[5] Toulouse Univ, CGI, IMT Mines Albi, Castres, France
关键词
Medication Use Process; Medication error; Requirement; Data Science; Reporting; Classification;
D O I
10.1109/AICCSA59173.2023.10479309
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Medication errors associated with the Medication Use Process present significant risks and require effective management. However, current practices do not address these risks. There is a lack of awareness that medication errors are unintended risks, and a lack of dedicated systems to manage them. To overcome these limitations, a digital system exploiting massive medical data (big data) is proposed. By integrating various data sources, this system aims to provide adaptable medication errors' management and continuous improvement. This article presents an overview of the system requirements and highlights the potential of Data Mining in healthcare. Implementing this system could revolutionize medication error management and improve patient safety.
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页数:6
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