Résumé
The digitization of hospital information systems is becoming widespread, enabling the increasing integration of interactive visualization methods into decision support systems. This development facilitates the anticipation of critical risks in monitored patients and helps reduce the workload of healthcare providers. However, Electronic Health Records (EHRs) contain large, heterogeneous, and temporal data. Then, providing tools to understand these complex data is a challenge. Using PubMed and Google Scholar, we conducted a search for articles using keywords related to time, visualization, and data. Out of 3,197 retrieved articles, we identified 111 relevant ones through clustering. Applying exclusion criteria to focus on implemented prototypes, we manually annotated 21 articles for our review. This exploratory literature analysis reveals that while this research area has garnered recent interest, it demonstrates limitations in the proposed solutions. Few approaches employ temporal axis distortion, and no approach in the medical domain visually integrates model predictions. The study highlights preferred functionalities for the visual representation of multivariate temporal data, such as parallel time series and hierarchical views.