Big Data in Healthcare: Hype or Hope – Learning Clinic White Paper
Article Synopsis :
The opportunity to bring together health data with information from many unrelated sources opens new doors.
“Big Data in Healthcare: Hype or Hope?” by Carol J McCall of the Learning Clinic introduces readers to big data and examines the possibility of harnessing it to transform healthcare. Per the paper, big data and its feeder technologies are becoming a force in the changing healthcare landscape as their use has, for example, led to 17% improvements in cardiology diagnoses and a 19% reduction in norovirus outbreaks.
The paper cites other examples of how healthcare institutions are using big data to improve diagnostic accuracy and speed, ignite health engagement, drive efficiencies in care operations, enhance treatments, and dramatically reduce the spread of infectious disease. Some of the key application areas include:
- Cardiology diagnostic accuracy
- Predicting onset of psychosis
- Speeding cancer treatment
- Targeting Metabolic Syndrome
- Diabetes management
- Reducing norovirus outbreaks
Big data innovations outside of healthcare will accelerate results in health and wellness. Given the growing pool of health-specific data generated from mobile devices such as smart phones, laptops, tablets and personal sensors, established players and startups are rapidly developing new techniques for actionable insight. Accessing, analyzing, and merging structured and unstructured data is the key enabler to data-driven healthcare.
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Digital Insurer's Comments
Ever cheaper and faster computing, combined with the development of affordable data analytics tools have made a huge impact on banking, retail and bioinformatics. The same ‘big-data’ forces are re-shaping wellness, healthcare and insurance.Tools are emerging to promote more targeted, effective preventative protocols and more personalized and optimized medicines, yielding better levels of care and lower healthcare costs overall.
Beyond the hype, skill building, infrastructure development, use case prototyping, and real time testing are the keys to riding this big data wave.
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