To move to value-based health care, organizations need advanced analytics to inform business and care delivery decisions. Raw claims data must be turned into information that can help optimize both cost and quality.
By acquiring, aggregating and refining multi-source health data, the 3M Intelligent Data Asset provides a comprehensive dataset to guide and support value initiatives. It is backed by 3M’s experience processing claims for more than 53 million lives and analyzing health care payment for more than 30 years.
Moving to value-based health care means it is critical that data accurately represent a person’s overall health and cost of care. Organizations need this data so they can share member information with providers, enter into shared savings contracts, change program policies, launch new insurance products, offer a plan on the health exchange, and countless other initiatives.
But acquiring, aggregating and refining data from various sources is a complex process, especially in health care. Data comes in many forms, and even claims data can vary from one payer to the next. Missing fields and claims, mismatched providers, inconsistent patient identifiers, conflicting dates of service and changing code sets can skew the results of your analysis, undermining your confidence in the data.
The 3M™ Intelligent Data Asset transforms your raw claims data into a repository of reliable, actionable metrics on cost, quality access and value. It gives you data that is fit-for-purpose, which means you get risk stratified metrics suited to your health care goals. It lays the groundwork for identifying—and acting on—value improvement opportunities.
Our system for data intake, processing and analysis avoids common pitfalls in harmonizing claims data from various sources by inserting hundreds of quality checks, which we’ve refined based on years of experience. This helps build data integrity from the very beginning, preventing costly mistakes upfront. Because we process 1.3 billion claims per month, we can better anticipate potential data issues.
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