In an effort to help healthcare organizations achieve more from their analytics – and better position them to take on new artificial intelligence and machine learning initiatives – InterSystems has launched a new service it's calling Clean Data as a Solution.

WHY IT MATTERS
InterSystems says Clean Data as a Solution helps its customers meet a key organizational imperative: ensuring their clinical, financial and operational data is able to be normalized, aggregated and interpreted more quickly and accurately.

Clean datasets – no duplicate records, formatting errors, incorrect information or mismatched terminology – are critical to even the most basic analytics projects.

The service – which the company says can help not just hospitals and health systems, but also payers, life sciences companies, contract research organizations and more – can help position health organizations as they move toward more AI and automation to help manage datasets from multiple sources.

Clean Data as a Solution offers product and data normalization functionality to support specific use cases such as integration, patient matching, aggregation, normalization, terminology and enrichment, de-duplication into a unified care record, clinical viewing capabilities and more, according to InterSystems.

It's delivered like other services typically included in a HealthShare Managed Solution: hosting, ongoing maintenance and operation, support, periodic upgrades and sophisticated security and data protection, officials say.

THE LARGER TREND
Data governance can be a big challenge for healthcare IT leaders. One survey asked 100 CIOs and CMIOs about their data governance efforts, and just 44 percent said they had an enterprise-wide data governance capability at their hospital. More than half (56 percent) said their governance efforts were incomplete or non-existent.

Nearly three-quarters of the CIOs polled (71 percent) said they'd experienced discrepancies between measures across organizational departments, such as those that traffic in clinical or financial data. And half said were big variations across clinical departments specifically – with organizational definitions vs. industry definitions, for instance, and with an understanding of previously existing business rules.

But good data governance and normalization is a non-negotiable part of any successful AI and machine learning initiative.

More basically, it's a foundational must-have for any health system looking to innovate its strategies to boost quality improvement, optimize population health management, drive operational efficiency  and more.

InterSystems points to Gartner research showing that the average cost of poor data quality on any organization is $9.7 million per year.

ON THE RECORD
"Quality healthcare is dependent on a pipeline of clean, reliable data which can be applied to all care scenarios," said Don Woodlock, Vice President of HealthShare, in a statement.

"There is no machine learning without data," he said. "Just as clean water is essential to public health, clean data is essential to digital health. Clean Data as a Solution offers providers, payers, and patients a clean data set to accelerate the application of AI and machine learning-driven insights."

Twitter: @MikeMiliardHITN
Email the writer: mike.miliard@himssmedia.com

Healthcare IT News is a publication of HIMSS Media.