suspect analytics

identify members with suspect and undocumented conditions

Our proprietary model helps identify members with suspect conditions and possibly undocumented conditions appropriate for prospective and retrospective targeting. This model individually considers HCCs and other factors that may indicate treatment of an unreported condition including prescriptions, DME, lab tests, therapy, and condition management. Based on the potential clinical and financial impact, we perform assessment and scoring work by identifying and ranking members with the highest probability of having missing or incomplete diagnosis codes. Our approach considers different levels of investment for each member based on a proprietary scoring model. Suspect Analytics considers multiple approaches for HCC recognition, ranging from retrospective chart review to prospective home assessment services with Primary Care Provider (PCP) notification and potential interventions.

features

  • Proprietary analytics utilizing member demographics and clinical rules based on procedure and diagnosis codes, lab results and other pharmacy and medical claims data
  • Aggregation and integration of large volumes of data
  • Customization of targeted conditions based on client ROI thresholds and risk focus

benefits

  • Increase potential revenue per chart
  • Focus your chart retrieval resources for greater ROI

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