Venture Beat: How Real-Time Data Management is Revolutionizing Healthcare
See Venture' Beat’s latest piece on the transformative potential of healthcare data. Select excerpts below.
Healthcare data streams continue to increase exponentially thanks to the influx of information from sensors and medical equipment. This has made clinical data processing increasingly complex. Electronic health records, medical imaging systems and clinical research databases generate a vast amount of data, presenting a formidable challenge for healthcare professionals who need efficient data management, accuracy and security.
Today, data analytics and self-learning artificial intelligence (AI) models have revolutionized how we manage, analyze and use data across industries. The healthcare sector is one where real-time data management and analytics are making major strides.
To tackle the mounting challenges of medical data management, the industry is turning to a patient-centric, data-driven approach, where real-time [and other real-world] data management plays a crucial role in facilitating patient services and supporting medical research.
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Real-time, real-world data enables healthcare providers to take prompt, proactive measures to prevent negative health outcomes, ultimately reducing the cost of care for patients. In fact, real-time data derived from real-world data sources enhances the effectiveness of care delivery across the healthcare continuum, improving outcomes for diverse patient populations that require precise, tailored treatment.
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Highlights on Atropos Health:
Brigham Hyde, co-founder and CEO of data-driven physician consultation service Atropos Health, said that a well-defined data architecture helps healthcare organizations capture, store and learn from their data securely and efficiently.
“Well-defined data architectures and sources provide additional context on the status of a patient or others like them — enabling rapid identification of patterns, trends, predictions and possible treatment plans via clinically-informed analytics technologies,” said Hyde. “These results can be used to provide more informed care, undercutting the healthcare disparities stemming from the evidence gaps for diverse patient groups.”
Hyde also said that real-time data, real-world data, and AI hold transformative potential for accelerating medical research and improving patient outcomes.
“We look forward to a future where there is widespread use in healthcare of technologies that make learning from clinical data faster, easier and more relevant to diverse populations,” Hyde said. “The output, for hospitals, is realizing the promise of the learning health system. For patients, it’s more tailored care based on aggregated evidence from the lived experiences of patients like them. And for science, it’s a road to augmented discovery and research potential.”
Unlocking the clinical impact of RWD is a driving force behind Atropos Evidence Network - the new observational insights exchange for healthcare data holders and insight seekers.