Posted by: adelvecchio
Healthcare.gov, predictive modeling
Guest post by Jerred Ruble, president and CEO, TeamQuest
The recent launch of HealthCare.gov has been met with more issues than anyone in the White House could have expected. While the results were unexpected, we’ve come to find that the root causes of the issues were fairly straightforward. So how did we get here?
What many in the technology industry understood immediately was that HealthCare.gov isn’t simply a website which hosts static information. It’s meant to be an application, one that relies upon a wide range of interconnected systems and data sources to provide timely and accurate data that is personalized to a certain degree for its users.
The myriad issues facing HealthCare.gov have been largely traced to a case of bad planning, specifically a lack of effective capacity planning — the process of ensuring the underlying systems had the resources available to handle the influx of Americans wanting to sign up. When the site went live, millions of uninsured Americans rushed to the website. What they were met with was long wait times, error messages, and more of a headache than a relief. It has been reported that at some points in the days immediately following the launch, there were 40,000 people in virtual “waiting rooms” because capacity had been reached.
In real estate, there’s a well-known mantra when it comes to selecting a home — “location, location, location.” When developing applications, there’s a similar thought process — “resources, resources, resources.” Specifically, the computing resources — the memory, storage, CPU cycles, bandwidth, etc. — required to ensure performance, stability and a positive customer experience. This is capacity planning at its core — the proactive approach of identifying the right amount of resources required to meet service demands now and in the future. It is a proactive discipline that allows IT to plan effectively and avoid surprise outages or performance degradations.
Let this be a lesson
Given the dynamic nature of Web-based systems and user requests, it’s hard — but not impossible — to predict the future with regard to necessary resource allocation.
Predictive modeling capabilities, a tool employed by innovative application developers and IT teams alike, can also be instrumental as a marketing differentiator. It allows providers to separate themselves from competitors through enhanced customer experience, pricing, and claims servicing. By making predictive recommendations of future resource needs, it allows providers to avoid costly outages or performance degradations. It’s also more efficient than a common solution employed by lots of organizations: overprovisioning. As the HealthCare.gov launch has shown, the opposite is what you want to avoid.
Insurers are expected to make improvements in their data and information management capabilities and implement a more sophisticated best practices approach to streamline their processes and become more proactive. Many will be looking to leverage IT to lower costs and increase quality while working to enhance the customer experience. Going forward, it will be critical to enhance the customer experience so providers aren’t left to compete on price alone. That starts with making sure systems are available and performing as expected.
With more than 30 years of software and management experience, Jerred’s passion and leadership have become hallmarks of his tenure at TeamQuest. Prior to his role as president and CEO, Ruble served as vice president of engineering at TeamQuest. He is one of the original partners who founded TeamQuest in 1991.