The Evolutionary Development of Hospital Data Analytics: Survival of the Fittest

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By Brian Wedderspoon, VP of Analytics Services at Sentry Data Systems

Medical technology is advancing at light-speed. Sequencing of the human genome is complete, the artificial pancreas is a reality, and the first pill embedded with a digital tracking sensor has been approved by the FDA. Yet when it comes to understanding and utilizing healthcare data, the pace of evolution is generations behind technological innovation.

So, what is holding data evolution back? The answer is complex—hospitals are strapped for time and resources, with little to devote to data management and analytics. Hospitals also face an over-abundance of data, with more coming in every day. Critical healthcare data is captured from multiple sources, including electronic medical records, admission/discharge/transfer (ADT) messages, billing and practice management, procurement, time and attendance, and general ledger systems.

Facing these kinds of challenges, there’s a certain level of expertise needed to move from collection to analysis to actionable application of data, and technology solutions alone can only take you so far.



The Pace of Evolution

Let’s look at healthcare data analytics as an evolutionary journey:

Data Collection and Management—The first step of evolution is simply realizing what information hospitals now have in their environment, then collecting and cataloguing it. As of 2016, “more than 60 percent of all US-based office physicians and more than 95 percent of all eligible  and critical access hospitals have demonstrated meaningful use of certified health IT through participation in the Centers for Medicare & Medicaid Services (CMS) Electronic Health Record (EHR) Incentive Programs,” according to the Office of the National Coordinator for Health Information Technology. That’s a lot of data to make sense of! Like our earliest ancestors, our first job as sentient beings is to assess and adapt to our environment; we’re just trying to survive with all this new information coming at us without being overwhelmed.

Data Analytics—The second step in data evolution is to start recognizing patterns in the data, making sense of the information you’re being given. Think of this as the period in human evolution when man started using tools and began to impact (rather than just react to) the environment around him. With data analytics, we can start to differentiate between wise and unwise decisions, using this information to logically predict outcomes.

Data Actualization—The end goal of data analytics is using the information to improve business process and strategies, impact bottom lines, and effect change in patient outcomes. Think of this as the time when humans started to develop language, and began to communicate their ideas to one another, collaborating on innovation to move the entire species forward.

The constant influx of data—from new patients, new systems, and new processes—is overwhelming and has made the challenge of moving beyond phase one of this journey an often insurmountable task. And even with a robust data analytics platform to help make sense of it all, hospitals still struggle to use the data to its full potential and uncover actionable insights.

An Evolutionary Advantage

To truly evolve in a way that ensures survival, hospitals and health systems need experts—those who have spent years perfecting the tools and the language—to help them advance.

The fact is that an analytics software solution is only as good as the team supporting it. With hospital and health system professionals under so much pressure, investing dedicated, in-house resources to deriving actionable insights from their data is a luxury many cannot afford. Professional analytics services, delivered by healthcare experts with a deep understanding of both the industry and the software, can be the missing evolutionary link hospitals need to reduce costs and improve patient care.

A professional analytics service team can help hospitals answer important questions along critical business dimensions, such as:

  • Strategic: Should we build a new orthopedic hospital? If so, where?
  • Financial: Are all my service lines profitable? Which ones are not, and why?
  • Operational: How productive is my labor force in each department? 
  • Clinical: What is the variability in drug utilization and cost contribution across physicians treating “like” patients?
  • Mission: At what rate have my Medicaid patients received flu vaccinations this year?  

It is these professional services, in tandem with a robust analytics software platform, that can help the industry evolve to reach its full potential, where we can start making an impact on the world around us. In the healthcare industry—as in nature—only the strongest survive.

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