Hackathon Insights: The Critical Role of Custom Data Selection and Aggregation in Longitudinal Health Analytics

Health data, with its inherent complexities, requires specialized data analysis and visualization solutions that enable effective data exploration and insight generation. In this article, we report on a hackathon focused on developing user-friendly, interactive solutions for health data analytics. Participants created a variety of prototypes with the aim of addressing the intricacies of health data, such as its hierarchical structure and longitudinal nature. Key challenges that were identified during this process include the need for flexible and customizable functionalities for selection, aggregation, and transformation of data. These functionalities should enable users to navigate and explore complex health data without requiring extensive data science expertise.