Improve Your Health Plan’s Risk
Adjustment Performance

Leverage Innovaccer’s solution suite for payers to meet your risk adjustment needs. Identify coding gaps based on clinical and claims data-driven analytics, covering both drop and suspect codes. Enable providers to prospectively improve coding accuracy by providing them actionable gap insights at the point of care, and unlocked improved retrospective review outcomes with NLP-facilitated coder chart review workflows.

telemedicine
regulatory
Identify drop or suspect codes
Analyze historical claims data and clinical documentation to identify drop codes and suspect codes. Run risk adjustment analytics to identify diagnosis codes and/or HCC codes supporting both prospective and retrospective review outcomes.
  • Aggregate claims and clinical data on members
  • Run analytics for drop codes (e.g., chronic disease diagnosis captured last year)
  • Run analytics for suspect codes based on clinical data (e.g., suspected diabetes based on lab results and medications)
  • Drive prospective and retrospective review workflows with open coding gaps inputs
fhir
fhir
Present open coding gaps to
clinicians at the point of care
During outpatient visits, present open coding gaps on
an EMR overlay interface. Drive prospective review
gaps closure right at the point of care.
  • Present open coding gaps at the point of care, covering relevant diagnosis and/or HCC codes
  • Provide details on supporting evidence, including underlying data sources
  • Enable provider-inputted gap responses
  • Directly integrate with EMRs to push accepted coding changes seamlessly into clinic notes
Leverage digital chart retrieval
for clinical data access
Connect directly with EMR systems for automated clinical data access on your members. Bring in structured clinical data and clinical documentation for downstream risk adjustment needs.
  • Utilize pre-built connectors to directly integrate with priority EMR systems
  • Capture relevant historical clinical data, and bring in ongoing updates on your members
  • Improve provider satisfaction with a seamless solution for clinical data access
fhir
fhir
Drive retrospective review via
coder chart review workflows
Closing coding gaps retrospectively with natural language processing (NLP)-facilitated coder chart review workflows.
  • Help coders maintain a worklist of prioritized tasks
  • Flag open coding gaps to coders, covering relevant diagnosis and/or HCC codes
  • Provide an encounter-based view of clinical documentation by member
  • Utilize NLP to automatically identify potential coding gaps and/or supporting evidence
  • Support reviewing of coder guidelines and resources to facilitate review efforts
Track risk adjustment
performance over time
Drive performance through highly customized dashboards that provide insights on operational and outcome metrics of interest.
  • View aggregate dashboards with views on risk adjustment performance over time
  • Drill-down into areas of lower performance across a range of parameters (e.g., HCC codes, providers)
  • Track operational metrics on efficiency of prospective and retrospective review efforts

Request a demo of our platform that turns data into outcomes.

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