MedisoftRx's Predictive Analytic solution has been measured against, and outperformed nationally recognized predictive analytic solutions.
Strategies to identify high cost members within a population often focus on high cost members in the current or prior period, using the population’s member as the unit of measure, i.e. “patient as their own control”. This approach ignores the “regression to the mean” phenomenon, i.e. majority of high health care cost members in one period will often regress to a lower cost in the next period.
MedisoftRx’s advanced Predictive Analytics engine utilizes a more realistic "Population" based strategy to identify current and future persistent “true” health care cost and risk drivers. This approach takes the guess-work out of identifying your target care management population.
Categorizing of population members into natural groupings based on demographics, chronic conditions, and other social health determinants allows for the identification of population subgroups, their characteristics and potential impact on current and future health care costs and risk.
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