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. 2019 Sep 16;16(18):3438.
doi: 10.3390/ijerph16183438.

Dementia Patient Segmentation Using EMR Data Visualization: A Design Study

Hyoji Ha  1 , Jihye Lee  2 , Hyunwoo Han  3 , Sungyun Bae  4 , Sangjoon Son  5 , Changhyung Hong  6 , Hyunjung Shin  7 , Kyungwon Lee  8
Affiliations

Dementia Patient Segmentation Using EMR Data Visualization: A Design Study

Hyoji Ha et al. Int J Environ Res Public Health. .

Abstract

(1) Background: The Electronic Medical Record system, which is a digital medical record management architecture, is critical for reliable medical research. It facilitates the investigation of disease patterns and efficient treatment via collaboration with data scientists. (2) Methods: In this study, we present multidimensional visual tools for the analysis of multidimensional datasets via a combination of 3-dimensional radial coordinate visualization (3D RadVis) and many-objective optimization (e.g., Parallel Coordinates). Also, we propose a user-driven research design to facilitate visualization. We followed a design process to (1) understand the demands of domain experts, (2) define the problems based on relevant works, (3) design visualization, (4) implement visualization, and (5) enable qualitative evaluation by domain experts. (3) Results: This study provides clinical insight into dementia based on EMR data via visual analysis. Results of a case study based on questionnaires surveying daily living activities indicated that daily behaviors influenced the progression of dementia. (4) Conclusions: This study provides a visual analytical tool to support cluster segmentation. Using this tool, we segmented dementia patients into clusters and interpreted the behavioral patterns of each group. This study contributes to biomedical data interpretation based on a visual approach.

Keywords: big data; bioinformatics; dementia; design studies; digital health; multidimensional data visualization; visual analytics.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Research framework.
Figure 2
Figure 2
Previous model 1: 2D node-link diagram and Parallel Coordinates.
Figure 3
Figure 3
Principle of RadVis Visualization.
Figure 4
Figure 4
Previous model 2: 2D RadVis.
Figure 5
Figure 5
Visualization combining 3D RadVis and Parallel Coordinates.
Figure 6
Figure 6
Result of segmenting dementia patient group into 5 clusters.
Figure 7
Figure 7
The result of segmenting patients on AD stage into 3 groups.
Figure 8
Figure 8
The result of AD stage segmentation using the Parallel Coordinates graph.
See this image and copyright information in PMC

References

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