Patsientide ravimikasutuse klasterdamine ATC koodide alusel

Date

2024

Journal Title

Journal ISSN

Volume Title

Publisher

Tartu Ülikool

Abstract

Healthcare data provides an opportunity to study patients’ drug trajectories. This thesis aims to create a workflow that clusters patients based on their drug use using ATC codes. In addition, a user interface is developed that can be used to interactively run the workflow. The workflow consists of 5 parts: filtering, drug trajectories compilation, drug trajectories comparison, drug trajectories clustering, and cluster analysis. As a result of the workflow, patients are divided into clusters, which are given a simple overview. The results can be used for further research to find the reasons for the different drug trajectories. The user interface consists of 4 parts. Its sidebar displays the main user inputs that can influence patient selection, clustering, and analysis. Tabs display the results of clustering and analysis. The results and the used parameters in the user interface can be downloaded as RDS and CSV files.

Description

Keywords

R, klasterdamine, aegridade analüüs, ravimikasutus, astma, clustering, time series analysis, drug use, asthma

Citation