Can big data influence inventory decisions at hospitals?

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Healthcare organizations are slowly but surely getting a handle on big data and using the information streams for a variety of different reasons. Gathering insights to impact hospital inventory management decision-making may just be the next forward-thinking strategy that ensures doctors and nurses have resources they need to respond to unforeseen circumstances. For example, researchers throughout the United States are finding ways to leverage posts on Facebook, Twitter and Instagram to learn where the next outbreak of the flu may be occurring.

Searching for the frequency of certain words that people post when they have the flu, as well as tracking the location, time, data, content, device used and username has allowed researchers to narrow down specific areas where there may be a higher concentration of people with the illness. Hospitals can then use these statistics to influence when they put in their next orders for materials. Being prepared for an outbreak can allow healthcare centers to treat more patients and potentially save more lives. The Centers for Disease Control and Prevention releases flu data every week, but it is often two weeks behind what is currently going on throughout the country.

"The advantage of using these social media tools and Google is they're much faster than the CDC," Michael Paul, a doctoral student working on a Johns Hopkins Twitter research project, told CNN. "As an early warning, they're useful to the government when it needs to plan."

The flu is just one example
Deadly outbreaks like swine flu and other illnesses demonstrate how harnessing social media information in big data streams can be worthwhile for healthcare organizations. Predicting when the next disease will become prevalent in the United States may make it easier to keep it from spreading.

Anil Jain, chief medical informatics officer of healthcare analytics company Explorys, told Becker's Hospital Review that population health management gives decision-makers at hospitals access to predictive models that can be shared with providers across the care continuum. With these resources in place, discovering health patterns throughout the world could create high potential for better, coordinated and specialized care.

"Lately, I've been using the term: bench to bedside to bottom line," he said. "The paradigm has shifted. The discoveries we are making with big data are informing decisions at a rate where the potential outcome - the bottom line - is more readily apparent."