Claims Analytics

Claims process improvement driven by artificial intelligence

Forget numbers…you need narratives.

Data can be overwhelming, intimidating, and cumbersome to interpret, even with a business intelligence tool in place. But in order to identify opportunities for process improvement, health systems need access to revenue cycle data, along with the ability to transform the data into the insight necessary to adjust and improve business practices.

Intuitively built, AI inspired.

SSI Claims Analytics was the first of our solutions to incorporate machine learning to provide clients with the ability to accurately forecast shifts in their bottom line. With easy-to-read visuals, the solution predicts when users will receive payments from payers, within a few percentage points. Unlike the tools of our competitors, our analytics solution aggregates all remittance data that comes through our clearinghouse and builds patient encounter logic for each patient, giving clients a full view into what is truly happening. With this leading edge machine learning technology, users eliminate time spent on manual reporting and, more importantly, the unexpected financial changes that can be detrimental to the health of an enterprise.

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“Using SSI has helped give us more visibility into information we use to drive our business. Knowing when, and how much, we will get paid is of the utmost importance. With this tool, we’ve reduced both manual efforts and uncertainty in understanding our cash expectations.”

– Christopher Richmond, Manager, Business Office Services, Northside Hospital

Read about Northside’s use of AI.

SSI Claims Analytics

Reduce uncertainty and determine how to make the greatest impact on your bottom line. SSI Claims Analytics provides hospitals and health systems with quick, seamless access to volumes of revenue cycle data, displayed in easy-to-read visuals that allow users to measure, track, and improve upon critical key performance indicators (KPIs). The solution delivers robust reports that allow for performance comparisons over time, along with industry benchmarking. Plus, the predictive remit capability, a machine learning feature, enables users to predict the timing and amount of payments from payers, thus minimizing manual processes and allowing the organization to prepare for potential dips in revenue.

Clients rely on the solution to provide leadership with instant—and accurate—answers to performance inquiries by logging in on their tablet or smart phone and getting a real-time snapshot of their organization’s revenue cycle trends.

Benefits

Visually interact with data for easier insight into revenue cycle operations
Quickly access KPIs to analyze financial performance
Easily identify trends and analyze historical data to identify problem areas within an organization
Accelerate cash flow by pinpointing payers above and below KPI thresholds
Develop an understanding of revenue cycle “drivers” to recognize more revenue and decrease operational costs
Minimize denials by examining the cause of issues and responding appropriately
Estimate cash flow via a predictive payment model that draws on data from claims sent out, rather than historical averages

How It Works

Armed with SSI Claims Analytics, health systems can develop a big picture approach to resolving revenue cycle challenges while simultaneously honing in on the most critical areas for process improvement. Visibility is possible from the beginning of the claim through payer response via a wide variety of user-configured views, from day-to-day operational details to high-level executive performance summaries … and everything in between. Drill down into the most important details affecting your organization and glean actionable information that can be used to develop, implement, and measure a performance improvement plan that aligns with your overall business objectives.

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“What we noticed was an ability to get to the level of detail necessary for process improvement, all in one precise location. The information is at your fingertips, which allows users to quickly and easily compare items or drill down to look at specific payer detail.”

– Jana Danielson, MS, FHFMA | Executive Director of Revenue Cycle, Nebraska Medicine

Full Case Study