Big Data In Healthcare

INTRO → BIG DATA AFFECT PUBLIC EXPENDITURE AND QUALITY OF THE SERVICE
The usage of big data in the healthcare sector can have significant consequences on the productivity of the healthcare system, improving the quality of care and treatment, enhancing patients’ experience, boosting industry competitiveness, and creating a range of fresh business models and services. For example, McKinsey has estimated that US healthcare could capture more than $300 billion in
value every year.
Interesting to see is that $200 billion out of those $300 billion derive from savings on national healthcare spending, that is of around 8 percent of the total national healthcare expenditure. It is necessary to go deeply into the repercussions of using big data on public

For example, 61 percent of respondents worldwide report they’re investing heavily in application modernization. While 64 % of IT leaders in all industries are investing heavily in big data, the number is 74 % among healthcare executives, who are using sophisticated analytics to determine which treatments are most and least effective, and which risk factors pose the greatest risk to patient wellness. Those analyses are producing real results, too, because 90% of surveyed healthcare say that big data is positively impacting productivity and efficiency. Healthcare organizations, meanwhile, appear to be more successful than firms in other industries at converting that increased IT spending into innovation. For example, 79 % of surveyed healthcare say their big data investments are positively impacting innovation, as opposed to 70 percent of all

The possibility of monitoring chronic illnesses leads to a more organized, structured and predictive way to approach patients, decreasing the need for treatment at general hospitals and cutting adverse drug events. Analyzing big data on healthcare, hospitals and clinics can predict and prevent crises, expand their preventive care offerings, optimizing the admissions and cutting the costs connected to them. Analysis of disease patterns and tracking of disease outbreaks and transmission are fundamental to improve public health surveillance, to have a faster response, to avoid predictable chronic situations reducing the need of hospitals admissions and to cut the costs related to waste of time and