A Framework for Discovering Latent Insights in Clinical Data

Document Type


Lead Author Type

CIS Masters Student


Dr. Jonathan Leidig; jonathan.leidig@gvsu.edu

Embargo Period



Amazon and Starbucks, two of America's most beloved brands, use data analysis every day to help understand their consumers. Mature data analysis frameworks allow organizations to uncover latent insights about their consumers behavior. These same data analysis techniques are not as common in the healthcare industry. With healthcare growing at a substantial rate, it is paramount healthcare organizations begin utilizing data analysis to improve patient care. By partnering with a local healthcare organization, it was possible to use exploratory data analysis to find key areas where business and clinical leaders could answer complex questions. The research was done utilizing Python which combined data from multiple sources, analyzed the data, and prepared the data for further analysis. R was used to explore, extract, and create visual representations of the data. Conclusions varied in significance and nature with some of the findings creating an appetite for further utilization of data analysis, some findings being suggestive but not conclusive and requiring further exploration, and some ideas produced no concrete findings due to data and timing constraints. Due to the confidential and proprietary requirements of the organization partnership, the research expands on broad ways data analysis can be used to improve patient care.

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