scholarly journals Validation of a Computerized Decision Support System To Review Pharmacotherapy Treatment: Scheduling Guidelines

Author(s):  
Clávison Martinelli Zapelini ◽  
Dayani Galato ◽  
Graziela Modolon Alano ◽  
Karina Saviatto Carvalho Martins ◽  
Silvana Cristina Trauthman ◽  
...  

Abstract Background In the pharmacotherapy review process, the pharmacist needs to list various information about the patient and the set of medications he will use, information that is never available at the point of care. Methods The aim of the study was to validate an intelligent information system, which was developed to assist the scheduling activity in the pharmacotherapy review process. The system used the concept of Genetic Algorithms. To validate it, appointments of hypothetical cases (ten) were made by the system and by human specialists. These schedules were qualitatively evaluated by pharmaceutical specialists with clinical and research experience in the pharmacotherapy review process. The degree of agreement between the assessments of the appointments carried out by the pharmaceutical specialists and by the system were measured using the Kappa index with a 95% confidence interval. Results In detecting errors, propositions, the system was able to identify 80% of errors, with human specialists identifying between 20% and 70% of errors. In relation to the general evaluation, the system obtained 87,3% of the compared evaluations, with the human specialist who came closest to this index obtained 75,5%. Conclusion It can be concluded that with the methodology used, the investigation met the objectives and confirmed the initial hypothesis. There are indications that the system can help in the Pharmacotherapy review process, being able to find prescription errors as well as to establish times for the use of medications according to the patient’s routine.

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 238
Author(s):  
Yuna Hur ◽  
Jaechoon Jo

A significant amount of digital cultural contents is shared online, but learners do not know where subject matter content is or how to find it. Therefore, there is a need for a service to improve educational quality by effectively providing relevant information in response to searches for content that is useful to learners. This study developed and tested the usability and utility of an intelligent information system that effectively searches and visualizes digital cultural contents. The system collects data on digital cultural contents, automatically classifies them, and creates content triple data to automatically display the results with a 3D timeline, knowledge network map, and keyword relation network map through content search, triple search, and keyword search. We also conducted a survey and in-depth interviews to verify users’ satisfaction with respect to the use and utility of the system. For the experiment, we developed survey questions to measure user satisfaction and conducted in-depth interviews regarding the system’s utility with a total of 65 subjects. The results show that the response for satisfaction with regard to the use and utility was generally “satisfied”. In addition, the system stability was evaluated as “high”.


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