Every year predictions surface about trends in technology, the economy and fashion, and what will be “in” and what will be “out”. In the midst of all the prognosticating, things can quickly explode across international borders and take our focus back to “real life” like the explosion of massive health epidemics from the flu to Ebola, and this year, the Zika Virus.

Behind all of it – trends, predictions and “real life” – is the collection of data, which plays a role in determining if events unfold as predicted. But in the healthcare arena, the aggregation of data leads important real-time insights about the spread of disease, which can lead to better allocation of resources in the short term and a better understanding of the disease in the long term.

As we have learned from past epidemics, such as Ebola and Avian Flu, we have to be able to track, identify, and isolate these diseases quickly in order to prevent a pandemic. Analytics are a big part of tracking outbreaks, and data collection is fundamental to epidemiologists’ ability to report and create epidemic trends and predictions.

All epidemics start on a local or regional level and this can make it more difficult for organizations, such as the Centers for Disease Control (CDC) or the World Health Organization (WHO), to recognize patterns or pandemic potential. I believe that when you begin to look at where cases present and how data is captured that a shared cloud infrastructure could play an active and important role in overcoming this obstacle.

There are federal mandates that require hospitals and clinics to report incidences of certain illnesses, such as cases of influenza, to the CDC. The challenge, however, is that there aren’t federal mandates for viruses that are not yet known to be issues. Coupled with that is the fact that hospitals and clinics use disparate systems to track and report information.  The end result of these disparate systems is that information becomes siloed, effectively trapped in internal systems – sometimes not even accessible between departments within the same organization – and information vital to identifying or tracking an epidemic can be lost.

We need to explore ways to connect these disparate systems and to create an ongoing – secure – way for an organization like the CDC or the National Institutes of Health (NIH) to capture that information. There is need, perhaps, for an epidemic exchange; a platform where data  from hospitals and research centers across the country, if not the world, can be analyzed and processed into valuable data sets to identify emergent epidemics.

As we all know, databases and repositories are tied together for insurance reporting purposes, so if there was a similar infrastructure for disease reporting and analytics, this would be a fundamental building block for an epidemic exchange.  To make the exchange concept really effective, however, a hybrid cloud infrastructure that brings together disease reporting metrics from all of the different private clouds to tie them together for the sake of early identification would be essential. Today, hospitals and clinics use private clouds, participate in public clouds and also participate in reporting. Unfortunately, many of them are tied into proprietary systems that would make it very difficult to participate in an exchange type of environment.

Finding a provider who can offer high levels of security in an open standards environment that allows for moving data from a private to a public or hybrid cloud – and back again, if necessary – is an important first step for research institutions, government agencies, and hospitals.  This becomes increasingly important when you factor in the amount of data storage required by healthcare providers.  Innovative healthcare data solutions that enable secure management of vast amounts of patient data are essential, as is the ability to use and share it enterprise-wide, and gain efficiencies of scale through cloud solutions and virtualization.

The explosion of data in the healthcare industry is just beginning.  Being able to store data in ways which keeps the information accessible and available will be a key challenge. Ensuring your vendor is one that can support your needs – in terms of rapid growth, changing needs and open standards – is imperative for healthcare systems for day-to-day operations, as well as aspirational activities like an epidemic exchange.

Interested in learning more about the latest developments in data analytics and storage in the healthcare industry?  Baylor College of Medicine is leading the way. See how they’re leveraging an easy-to-use cloud infrastructure to drive research and medical breakthroughs.

This month, in the lead up to HIMSS 2016, GovDataDownload will be running a series of feature articles for healthcare providers, healthcare payers, research institutions, and government agencies.  Why not subscribe to get stories delivered to your inbox?