The development of presentations medical information by data visualization

Abstract

BACKGROUND: Accurate, complete, clear, and timely processed information significantly enhances organizational decision-making efficiency. Data visualization is a crucial tool for this purpose. However, current information services of Chiangrai Prachanukroh Hospital are still in the form of raw statistics that are not readily usable.Consequently,the researcher aimed to develop a data visualization-based information service model to make information easier to understand, faster, and more effective.

OBJECTIVE: To develop a model for presenting medical information using data visualization techniques and to compare the level of satisfaction with this presentation model against the conventional model.

METHODS: An action research approach, consisting of planning, action, observation, and reflection, was used. Data werecollected from hospital information system users through four consultativemeetings. Satisfaction data was collected from a sample group of 150 respondents. The studywas conducted between October 2024 and September 2025.

RESULTS: The developed data visualization presentation model emphasizes presenting informationin a visually understandable format, such as the use of charts, maps, trend graphs, and tables. After trial use, most users reported that the data presentation was more interesting, aesthetically pleasing, convenient, user-friendly, and immediately usefulcompared to the conventional model. The sample group showed significantly higher satisfaction with the visualization model in terms of definitions, management, and overall presentation compared to the conventional model. The factors that influenced the level of satisfaction included age (p<0.001), experience (p=0.037), profession (p<0.001), and the purpose of data use (p<0.001).

CONCLUSIONS AND RECOMMENDATIONS: The developeddata visualization presentation model makes data use more convenient, faster, interesting, and immediately useful compared to the conventional model. Further development is recommended in areas such as presenting a greater variety of data, increasing processing speed efficiency, enhancing understanding of data definitions, and adding channels for frontline staff to contribute data.