ARTICLE: How real-time data management is revolutionizing healthcare

Healthcare data streams are increasing exponentially, making clinical data processing increasingly complex. Data analytics and AI models are revolutionizing how we manage, analyze and use data. Real-time data management is essential for healthcare professionals to provide better patient care and enable medical breakthroughs. It can yield benefits such as reduced treatment costs, a comprehensive understanding of patients and their conditions, and optimized workflows.

How real-time data is enhancing healthcare services

Real-time data management and analysis can improve quality of care by empowering providers to influence clinical encounters.

Better medical decision-making

Real-time data enables healthcare providers to take prompt, proactive measures to prevent negative health outcomes, reducing the cost of care for patients. It also enhances the effectiveness of care delivery across the healthcare continuum, improving outcomes for diverse patient populations. By implementing real-time data, clinicians and public health professionals can improve coordinated care efforts, patient outcomes, and cost of care.

Clinical trials and medical devices

Nvidia and Medtronic have collaborated to integrate Nvidia Holoscan and Nvidia IGX with Medtronic’s GI Genius AI-assisted colonoscopy system to detect early signs of colorectal cancer.

A seamless data architecture for managing healthcare data

Healthcare delivery relies on a cohesive ecosystem of surgical tools, connected sensors, radiology imaging, EMRs and other applications that must work together to provide a comprehensive picture to surgeons, clinicians and interventionists. Data flow and architecture must be understood to ensure effective and efficient healthcare delivery.

Accuracy through connection

Accurate healthcare data is essential for making informed decisions that affect patient care. A connected data architecture is essential for reducing errors, streamlining the flow of information, and minimizing the need for manual data entry. Real-time data enables workflows and solutions with uptime, while enterprise-class solutions help capture, store, and learn from data securely and efficiently. These results can be used to provide more informed care.

Controlling the flood of healthcare data

The increasing amount of collected measurements presents clinicians with a deluge of data, which must be transformed into actionable insights. AI language models like ChatGPT and GatorTron can aggregate multiple data sources into a consistent view or write a clear summary of large quantities of data to provide insight into a patient’s condition. Healthcare providers face security concerns, standardization issues and the need for more robust tools. A fundamental shift is needed, not only in the technical realm but also in the comprehensive design and management of healthcare processes.

What’s next for real-time healthcare data management?

Niewolny and Hyde both believe that real-time data, real-world data, and AI have transformative potential for accelerating medical research and improving patient outcomes. Niewolny believes that multi-modal applications will become more prevalent, providing clinicians with additional insights. Hyde believes that this will lead to more tailored care based on aggregated evidence.