Generative AI Applications In Healthcare Data Mart Design And Optimization

Abstract

Generative AI enables novel applications across multiple domains. In healthcare, responsible implementation promises improved data governance, better decision support, and reduced risk of data breaches. Generative AI can also enhance healthcare data marts, improving the design, integration, quality, optimization, and usability of data for analytics and artificial intelligence. Specific applications include schema design, storage optimization, and data modeling for artificial intelligence. Using simple, practical language, concepts are described from a generative AI practitioner perspective.

This work extends the healthcare data mart framework proposed by Ceglowski in 2020. Data integration combines sources across on-premises and cloud environments, ensuring quality and reliability. Storage optimization techniques decrease costs while boosting performance. Generative AI identifies critical features and the expected evolution of population cohorts. Results support decision- making in analytics solutions on infectious diseases and chronic care during the COVID-19 pandemic, with parallel applications in other public health crises.