Overburdened Healthcare IT Systems Can Be Detrimental to Predicting and Containing Epidemics
By James D’Arezzo
Underperforming IT systems in the healthcare sector can inhibit the ability to predict and contain infectious disease epidemics. A timely example is the current measles epidemic, which healthcare organizations were unable to predict and have been slow to curb.
The Journal of Infectious Diseases special supplement, “Big Data for Infectious Disease Surveillance and Modeling,” indicated that there are significant challenges to overcome in acquiring and analyzing important real-time data that could offer important insight into current and future disease outbreaks.
One report in the supplement states that “the last 10 years have seen dramatic advances in data collection and digitalization, finally allowing the construction of a portfolio of data-driven epidemiological models. The increasing number of available models and the lack of best practices in integration and data sharing are however major roadblocks in the development of the field.”
Predictive analytics and modeling require massive amounts of data from many sources with thousands of variables, but experts say that predictive analytics in healthcare lags far behind fields like meteorology and marketing.
U.S. healthcare IT infrastructures must be able to process and analyze growing volumes of complex data. Underperforming IT systems impede potentially life-saving predictive analytics and predictive modeling capabilities.
Tsunami of Data
The volume of big data is expected to grow faster in healthcare than in virtually any other sector over the next seven years, according to an International Data Corporation report.
Researchers found that healthcare data is projected to grow through 2025 at a compound annual growth rate of 36 percent, faster than that of manufacturing (30 percent), financial services (26 percent) and media/entertainment (25 percent).
Alarmingly, IT investment in healthcare is among the lowest of all industries, the report states. IT departments are forced to try to overcome data challenges while also investing in technologies like robotics and edge computing.
IT System Performance Issues
Performance degradation progresses as the input/output (I/O) movement of data between the storage and computer/presentation layers declines. Analyzing data is slower than acquiring data, but it can become much faster by optimizing server and storage performance.
If I/O drags, performance across the entire system slows. This primarily impacts computers running on Microsoft SQL servers, which is the most popular database in the world. The Microsoft Windows operating system is also notoriously inefficient with I/O.
I/O degradation is more common than most organizations realize. More than a quarter of organizations surveyed last year reported that poor performance from I/O-heavy applications was slowing systems down.
Hardware Not the Answer
Computers are getting faster, but performance issues still cause slower applications, system crashes and long processing times.
While investments in storage and infrastructure will be helpful to a degree, big data is primarily a matter of processing information at a certain speed. That speed depends on the overall system’s I/O efficiency, on which additional hardware has limited impact. Even though new hardware can promise more I/O per second, data filled with small, fractured, random I/O quickly becomes unmanageable.
Hardware vendors are taking advantage of these issues and spreading misconceptions that new hardware is the only solution to performance problems.
Hospitals and other healthcare organizations are spending billions of dollars on hardware—at least some of which is unnecessary.
The American healthcare industry is already wasting up to $1.2 trillion a year on completely unnecessary processes – $88 billion due to the ineffective use of existing technology alone.
Software is the Solution
Maximizing the capabilities of an existing system is far more economical than expensive hardware upgrades, of course.
Luckily, I/O degradation is a software problem, one for which relatively inexpensive software solutions exist that can improve overall system throughput by 30 to 50 percent or more in the Windows environment.
This is a cost-effective solution that healthcare IT leaders need to pursue—lives depend on it.
About the Author:
James D’Arezzo is CEO of Condusiv Technologies, the world leader in software-only storage performance solutions for virtual and physical server environments.
