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How Data Integration Can Save Lives and Economies During Pandemics



Contributed Commentary by Ravi Shankar

May 20, 2020 | Advances in medicine, aided by technology, have saved many lives, no doubt. Proof? The global life expectancy of humans has doubled in the last century. Credit can be given to many technologies, both hardware and software, starting with the simple stethoscope to complex CATSCANs, and Electronic Medical Records (EMR) but when a new kind of viral disease comes along such as the coronavirus, we are once again humbled.

Modern data integration approaches and new cloud-based technologies are making an impact on disease management and discovery by bringing together data from disparate sources and providing a real-time unified view—whether it be about patients, citizens, or businesses. Data integration can help save lives at the point-of-care in hospitals, and help healthcare agencies to contain outbreaks, while reducing the economic losses due to decreases in manufacturing and trade.

Data Challenges Can Worsen Outbreaks

Outbreaks such as the coronavirus become even harder to tackle when pertinent information is not made available to physicians at the point of care or to agencies such as the Center for Disease Control. This lack of information prohibits care givers from quickly determining how to contain the outbreak, and thwarts efforts to mitigate trade shortcomings, and improve supply chains.

The problem is that the information these constituents need is dispersed across multiple data sources. In hospitals, data about patients is spread across different systems and departments: EMRs, clinical systems, emergency department computers, pharmacy systems, and the list goes on. In health agencies, geographical data pertaining to where the outbreak is worse, where it is starting, and where workers might be able to contain the disease in terms of the number of hospitals, beds, and trained healthcare workers, is scattered across numerous government departments. And private businesses are even worse off in this respect as they store information on-premises, in the cloud, and across third-party systems that inhibit them from quickly moving the production to a different location to offset the decrease in output from any affected locations.

These disparities highlight the need for integrated information to be delivered to physicians, business analysts, and/or government workers at the required time to effect change.

Time is of the Essence; The Need for Real-Time Information

Even if the data is stitched together into an integrated view, it does not help the cause if it does not arrive in time. To treat a patient, doctors need the information when a patient checks into the emergency department. More specifically, they need to know the patient’s symptoms, past medical history, and any allergies to food or medication. Businesses need to quickly know how their production capacity may be affected at a certain location when there is a shortage of employees or raw materials, or the government orders them to shut down. Healthcare agencies need immediate access to information to dispatch the necessary healthcare workers, medications, and equipment to arrest the spread of the disease. Finally, the government also needs the information to inform the public in a credible way, to avoid panic and further worsen the situation.

How can information be integrated across data silos and delivered in real time to the point of decision making? A modern data integration method called data virtualization is one approach.

Rectifying the Issue with Real-Time Data Integration and Delivery

Often considered a “data fabric” because of its ability to stitch together data from all of the disparate sources regardless of the location, the format of the data, or the latency with which the data becomes available, data virtualization delivers information in real time and in the format required by each individual data consumer. And it does so by furnishing each data consumer—the healthcare worker, the agency and the business executive—with a view of the source data without stopping to replicate the data for curation or transformation.

Many healthcare and biopharma companies are already leveraging data virtualization to consolidate and accelerate data access. BioStorage Technologies, a leading provider of sample management services to the scientific research community, leveraged data virtualization to build a new data infrastructure that delivers critical information and data for the genome-specific treatment of life-threatening diseases. National Services Scotland (NSS), which delivers healthcare-related services as a national board of Scotland’s broader National Health Service (NHS), relies on data virtualization to enable a variety of new functionality including an enhanced cancer intelligence platform and a person’s-at-risk dataset, for use by local authorities and government agencies in times of emergency, as well as a national radiology dashboard.

Hospitals are also benefitting as the largest university hospital in The Netherlands, Erasmus University Medical Center, uses data virtualization to create a future-proof data platform from which doctors, staff members, and researchers can access the data they need with the tools of their choice. The new platform facilitates management via Key Performance Indicators (KPIs) that are centrally used throughout the entire organization. Using data virtualization to deliver integrated, 360-degree patient health views directly to physicians, hospitals could provide information about recent hospital visits, test results, and medications patients can and cannot take, to help guide the treatment protocol at the point of admission or triage.

Likewise, healthcare agencies can use data virtualization to assemble real-time information from hospitals about the number of coronavirus diagnoses and visualize concentration maps within business intelligence tools, to determine the most effective containment logistics. Research institutions can use the technology to deliver disease details directly to their researchers, straight from the hospitals as patients are being diagnosed, to accelerate the discovery of a vaccine.

Businesses can use data virtualization to reroute logistics across plants and locations while government agencies can use the information to reassure the public about the steps they are taking to protect citizens. If data virtualization can integrate data and deliver it in real time to the right people, can it help global efforts to mitigate the spread of the coronavirus pandemic?

Yes, it can! Some technology companies have launched initiatives to do just that. Here is one for example: Coronavirus Data Portal is an open, collaborative platform that uses the power of data virtualization to integrate various COVID-19 datasets from across the world and make the combined data available to researchers to help accelerate solutions to this deadly disease.

How Data Integration Can Save Lives and Economies

As of today, the coronavirus is spreading like wildfire and jumping across continents. There are travel restrictions, factories have stopped production, and schools are closed. Manufacturing is down, and so is the stock market. There is no vaccine in sight, and by certain forecasts, there won’t be for another year. The end seems so far away.

While data integration and data virtualization are not the panacea for the outbreak, they can certainly help global efforts by quickly providing an integrated view of the data so that response teams can gain the upper hand. Just as the outbreak started with people and cascaded down to businesses and across countries, the remedy has to start at the top with people as well, before the remedy is felt by businesses, borders, and economies.

As with Ebola, SARS, and other pandemics, coronavirus will ultimately be overpowered. Technology will once again help with the first line responders. Data virtualization will do its part by helping people and organizations to have all the relevant information at their fingertips, so that we can put an end to this disease once and for all.

Ravi Shankar is senior vice president and Chief Marketing Officer at Denodo, a leading provider of data virtualization software. For more information visit https://www.denodo.com or https://twitter.com/denodo. He can be reached at rshankar@denodo.com.

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