User configurable logic to define variables related to interactive diseases. For example, beneficiaries with both diabetes mellitus (HCC 15 to 19) and congestive heart failure (HCC 80) are considered for additional risk adjustment scoring
► Average impact on RAF score and associated dollars
► Visualize/drill-down RAF/dollars impact by various parameters related to beneficiaries
► Net scoring of HCCs based on number of beneficiaries
► Impact analysis at each beneficiary level
MVision has been customized to include data elements related to HCC coding and Risk Adjustment Modeling.
Disease hierarchies address situations when multiple levels of severity for a disease, with varying levels of associated costs, have been reported for a beneficiary
Example of customized parameters while running a model for RAF scoring
Impact analysis
RASS takes in data from various sources and subsequently several data transformations, HCC modeling and application of RAF scores are on the billions of records.
MCheck offers a scalable and easy to maintain solution that can be easily plugged into input/output points of the overall process.
► The manual nature of the deterministic approach which is therefore subject to substantial error
► Organizations take months to define and fine-tune such rules
► Performance of a deterministic data quality analysis being severely impacted due to the enormity of data
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