• Hospitals and health systems face staggering staff shortages across the revenue cycle, disrupting collections and ultimately their capacity to treat patients. There’s a clear imperative for revenue cycle leaders to do more with fewer people, but spotting workflow inefficiencies across a distributed workforce and IT landscape is an enormous challenge. Add to that a lack of in-house expertise to analyze and prioritize potential interventions, and leaders are tasked with the impossible.
• Part of Janus Health’s Operational Intelligence suite, Process Intelligence uses our proprietary process mining tool, Observe, to measure the complexities of your workflows and then applies AI to that data, identifying and quantifying areas for improvement. Process Intelligence surfaces those insights in a user-friendly application, empowering revenue cycle leaders to confidently recognize, implement, and measure meaningful process changes.

Janus Health is fundamentally transforming the future of revenue cycle work with our groundbreaking end-to-end artificial intelligence platform. Our rich history in healthcare and technology allows us to instinctively understand what it is about revenue cycle management that creates significant challenges for healthcare organizations. We’ve developed Operational Intelligence and Intelligent Automation solutions to aid revenue cycle teams in optimizing their workflows, so they can do more with less and ultimately collect more cash.

Payers constantly change the rules. Sift evens the playing field. Sift equips healthcare organizations to fully leverage their payments data to work smarter, protect their margins and accelerate cash.

Actionable Denials Intelligence, delivering a longitudinal view of clinical, coding, claims and remittance data. Sift establishes a data foundation that gives providers unprecedented access to their payments data and intelligence tools to better manage their denials, identify root causes and prevent future denials. 

• Unified, normalized and organized claims and remittance data.
• Delivering an accessible and complete picture of claim behavior, payer trends and the drivers of denials.
• Curated, consultative analysis pinpointing where your team can take action to prevent denials and optimize workflows.

Denials Prioritization & Intelligent Automation to better manage touches and lower the cost of delivering each dollar of cash.

• Sift’s machine learning optimizes workflows by prioritizing your team’s denial work efforts around ROI and by delivering Smart Claim Edits that improve first-pass yield. 
• Active-Learning Claim Scrubber analyzes daily claims and remittances to curate high-impact claim edit recommendations.
• Machine learning models that score denials at an atomic claim level, using over 500 attributes to determine each denial’s likelihood to overturn.
• ROI-based denials worklists seamlessly integrate into your EMR, prioritizing high-recovery denials in staff workqueues.
• Scoring that enhances existing automation capabilities, enabling the strategic automation of low-yield accounts while avoiding over-automating recoverable accounts.

Denials Prevention. By unifying clinical, coding and payments data, Sift's ML predicts denials before claims are created and provide recommendations for upstream interventions. 

Sift’s ML models predict the likelihood of denial and provide pointers for intervention and prioritized user analysis, working to optimize payment outcomes.

• Machine learning models score encounters around their likelihood of being denied, proactively flagging encounters for intervention before claim submission.
• Denial category prediction and root causes pointers enable routing to the appropriate mid-cycle workflow for mitigation.
• Mid-Cycle Denials Intelligence that ties back-end billing, denial and overturn patterns to upstream workflow data inputs to deliver root cause analysis and prevention recommendations.

Process Intelligence captures actions taken both in and outside the EHR, providing a more complete picture of workflows across systems and teams.

Traditionally health systems employed over-the-shoulder consultants for this workflow data. Process Intelligence is superior in a few ways:

• It’s unobtrusive and unlikely to affect user behavior, leading to a more accurate representation of workflows and activities.
• It’s deployable to all system-owned, Windows machines, regardless of work location.
• It’s measuring today and for as long as it’s installed, allowing you to compare time periods and measure the effectiveness of interventions.

1. ML to predict propensity-to-overturn, enabling dynamic denial prioritization -- rather than rules-based systems (i.e. EMR offerings).
2. ML to predict propensity-to-deny, enabling denial prevention before claims are created. 
3. Rev/Track Insights Reports with curated intelligence and action items.
4. Unified and accessible data foundation, including:

• Matched claims and remittance data
• Unified and normalized payments data
• Payments data matched to corresponding CDI and coding data.