Transforming Healthcare Data Engineering: Driving Scalable, Accurate, and Impactful Decision-Making

Abstract

The healthcare industry creates a huge amount of data every day, from patient records, enrollments, medical devices data to insurance claims and lab results. Many healthcare systems find it hard to manage this data because of problems like outdated technology, heterogeneous systems, data silos, and issues with data quality. These challenges make it difficult to use the data effectively for better decision-making and improved patient care. This article explores how modern data engineering is helping healthcare organizations handle their data better. New tools like cloud systems, real-time data processing, and artificial intelligence are making it easier to combine and clean data from different sources. With these advancements in data engineering, the healthcare providers can make faster and more accurate decisions. This process improves patient care, reduces costs, and helps manage resources more efficiently. Examples like predicting patient readmissions and monitoring ICU patients in real-time show how this approach can make a big difference. The article also looks at new ideas like using AI that can explain its decisions and faster data processing with edge computing. Modernizing healthcare data systems is critical for creating better outcomes for everyone.