Data-Driven Insights and Tools to Optimize Care and Funding

Apply the power of your network’s clinical data to yield better insights, better care, and better outcomes across all VBC arrangements. Edifecs combination approach includes simplifying contracting and administration while gaining real-time performance insights with our value-based payment contract offering alongside an NLP-enabled clinical risk adjustment workflow. Marrying the two for a comprehensive solution helps providers tackle the pervasive challenges that prevent VBC success including inadequate documentation, incomplete coding, and tenuous VBC contract negotiations and performance measurement.

Infographic - Healthcare Providers

Products


Value-Based Payment Performance Management


With Edifecs value-based care solution, both payers and providers have access to data and insights to support value-based initiatives from joint program design to deployment, including continuous monitoring and optimization of value-based program performance.

  • Improve trust in the quality of data with advanced processes in data collection, validation, transformation, integration, and aggregation for a single source of truth
  • Gain real-time insight into financial, quality, and contractual performance, which facilitates continuous monitoring and optimization of value-based arrangements
  • Leverage advanced analytics to identify potentially improper payments with extensive data views, interactive dashboards, and meaningful alerts

Contract administration and performance monitoring software and analytics that simplify and streamline APM participation

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NLP Suspecting


Dig deeper into unstructured data to surface conditions not previously diagnosed but anticipated based on our AI model’s clinical evidence review. Findings come from a combination of disparate data sources to surface unrecognized conditions, undocumented instances of complexity, or comorbidity. In each case, a possible suspect is determined through the blending of criteria that includes available data points and assessment through rules-based and complex logic.

  • Generate a more complete and accurate list of suspected conditions with both administrative and clinical data for provider validation
  • Throttle suspect volume with confidence scoring, suppression, and filtering at both the global and local level, including care specialization condition targeting
  • Confirm up to 20-25% more valid conditions resulting in a potential +10% RAF value

Identifying conditions not previously diagnosed but anticipated based on our AI model’s clinical evidence review

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Risk Adjustment Workflow


Risk adjustment in a clinical setting is prospective, aligning itself with clinical workflows and goals by surfacing conditions - suspects - not previously diagnosed but anticipated based on clinical evidence (claims, pharmacy, diagnostic tests, etc.). These suspects can be routed to the care team directly at the point-of-care, or they can be curated by a review team pre-encounter for increased likelihood of acceptance.

  • Attain net-new RAF capture by surfacing undiagnosed conditions mined from unstructured clinical data via EHR workflows
  • Enhance care plan effectiveness and clinician’s time in-treatment with more complete risk capture and patient documentation, inclusive of all comorbidities
  • One single solution across all contracts, payers, populations, and EHR systems

A modular, EHR-integrated solution that identifies, manages, and documents population risk

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