Guest Column | April 12, 2018

Give Healthcare Teams What They Want In Data Analytics

By Anuj Gupta, CitiusTech

Business Analytics

Consumers today expect technology to be not only fast, but readily available and intuitive as well. With smart phones, tablets and other everyday technologies, we have become accustomed to searching for and finding what we need instantly. Healthcare informatics professionals are no different. Just 10 years ago, people accepted that software might take longer to answer a question, run calculations or even move to another screen. A recent report highlights just how quickly this has changed. In 2006, the average online shopper expected pages to load in four seconds or less. Today, 49 percent expect load times of two seconds or less, and 18 percent – one out of five – expect pages to load instantly.

While people’s expectations continue to be shaped by retail experiences, their expectations are often exaggerated by their perceptions – or misperceptions. According to the same study, people perceive load times to be 15 percent slower than the clock states. This perception of slowness adds pressure to architects, engineers and developers to achieve speeds that often conflict with the demand of the task. This is especially true for those healthcare professionals tasked with measuring, monitoring and driving actions based on key regulatory, contractual and operational metrics. Continuous advancements in technology have reset expectations, erasing any allowance that once existed for a trade-off between speed and task complexity. People now demand both instant and accurate results.

The Impact Of Growing Data Volume

A key challenge is data. As data sharing among payers, providers, health systems and government agencies grows, the volume of data generated every second also grows exponentially. All this data must be managed efficiently while quickly and accurately generating reports to meet the demands of accountable care organizations (ACOs), Healthcare Effectiveness Data and Information Set (HEDIS), Merit-based Incentive Payment System (MIPS), Medicare Access and CHIP Reauthorization Act (MACRA) and more. Healthcare organizations need to employ effective tools for working with huge amounts of data at high speeds – real-time and near-real-time – using features, such as replication, horizontal scalability and high fault tolerance.

Just as critical as expectations are for speed, users’ expectations for the overall experience are also high, which have also been strongly influenced by retail experiences. Users want the experience of managing advanced analytics to be intuitive and enjoyable. In response, many healthcare IT companies have been answering the call to deliver products. And considering that the U.S. Healthcare industry is projected to grow to $5.5 trillion by 2025, there is much economic incentive to continue.

Enabling Speed And Flexibility In Business Intelligence

Business intelligence applications rely on rules engines to query and analyze vast amounts of data efficiently. New reporting rules yield more complexity – more data sources and types, more analytics tools and more integration needs. Today’s rules engines have an uphill battle to earn and maintain credibility when it comes to delivering the technical, behind-the-scenes requirements.

The need for tools that provide an easy-to-use, do-it-yourself interface for rules management is in great demand. Business users must be equipped to easily configure, audit and operationalize clinical quality measures (CQMs), cohorts, clinical alerts and other rules without dependency on IT and without manual intervention.

In this environment, migrating rules engines to a high-performance, database-agnostic engine is a game-changer. With this approach, organizations can adjust to changing business requirements on the fly and run ad hoc analytics, which require massive amounts of behind-the-scenes computational power. The ability to scale up and down without having to wait – while providing an outstanding user experience – requires expert design, power and architectural framework.

In addition, rules engines that take advantage of Java can deliver speed and turnaround from as low as milliseconds up to only one second. For healthcare organizations, this means that for a single patient, the output of real-time processing for multiple measures happens within milliseconds.

At the same time, the benefits of being database agnostic cannot be underestimated. This means different types of organizations – payer, provider, medical technology – can easily take advantage of the rules engine to provide the horsepower needed for their specific analytics and reporting needs. Because organizations rely on many commonly used databases, such as SQL, Netezza, Redshift, and others, rules engines that are dependent upon a certain database environment will not survive.

The computational and processing capabilities of this data and analytics environment make meeting seemingly impossible consumer demands to process huge volumes of data with utmost accuracy a reality. The result is enabling healthcare professionals with the best tools for effective, data-driven decisions for their regulatory, clinical, financial and operational metrics, leading to improved patient care and decreased healthcare costs in today’s value-based care environment.