Doctor utilizing RevAware's machine learning, large language models, and natural language processing help overcome multi-modal data challenges

RevAware

RevAware icon

Practical data science to accelerate performance.

RevAware empowers financial leaders with data science, utilizing predictive analytics, graph neural networks, and deep learning for rapid workflow deployment. Our business intelligence tools enhance transparency into processes and performance, guiding optimal staff positioning and accountability.

Our machine learning, large language models, and natural language processing help overcome multi-modal data challenges, enabling your organization to leverage the diversity of patient, provider, and payer data for a powerful strategic advantage.

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Real Results

Faster Throughput: 4.0 Days reduction in DNFB days achieved through quick wins
End-User Benefits: 113 revenue cycle staff members experiencing improved workflow
Financial Performance: $21M cash acceleration within first 60 days of deployment

Key Features

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Productivity & Performance Monitoring

Enable consistent workflows and accurate productivity assessments by aligning standards with actual staff workload based on complexity.

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Dynamic Staffing Models

View real-time assessments and ensure aligned roles and responsibilities based on workload complexity, maximizing efficiency and cost-effectiveness.

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System Cohesion & Interoperability

Uncover and mitigate low-impact, high-frequency issues that disrupt staff efficiency, while pinpointing opportunities to refine RPA and system edits.

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Algorithmic Workflow

Quickly configure and deploy algorithmic workflow with predictive analytics, graph neural networks, and deep learning.

New Levels of Complexity Require New Methods

Existing healthcare technology is not robust enough nor flexible enough to consistently deliver what is needed.

Worklists Before RevAware

Data visualization with convoluted, unclear claims data with hindered efficiency of the billing lifecycle

Before the implementation of RevAware, claims data was convoluted, lacking clarity across payers. Managing DNFB edits was challenging due to workflow bottlenecks, creating performance variations that hindered the efficiency of the billing lifecycle, thereby inflating cost-to-collect.

Worklists After RevAware

Data visualization with more organized claims data, due to identified bottlenecks, predictable performance variation, and pattern-driven, operational workflows

After deploying RevAware, DNFB edits are now effectively preventing denials, bottleneck anomalies are instantly identified, the true costs of performance variation are predictable, and the workflow exhibits a linear, pattern-driven operational state.

Ready to learn more?

Contact us today to learn more about how RevAware can benefit your organization.