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Socio-Economic Attributes

A recent innovation in the realm of predictive modeling and population stratification is the development of socio-economic attributes, primarily from public records data. This capability is a game changer in health care allowing the adjustment of individuals' clinical risk and cost driven by non-claims events. This provides great insight into the health of plan members, allowing a health plan to better assess clinical risk or medical cost of those individuals.

The Stress Index was created to increase the accuracy of predictive analytics, representing the first meaningful industry integration of medical and pharmacy claims information with socio-economic data from outside sources. With the integration of socioeconomic data, the Stress Index, accurately predicts patients at a high risk of experiencing the onset or aggravation of health conditions brought on by high levels of stress which cannot be detected with medical or claims data alone. About 90-95% of a population' clinical risk and cost is known through claims-based predictive modeling. The remainder are generally considered random events, such as car accidents and broken arms, that are not predictable. With Socioeconomic data you have the ability to predict that "random" risk, as trauma or stress induced events.

A large database of public and private records that contain billions of public and proprietary documents including name/address combinations, property records, and legal records were used to identify 283 attributes linked to clinical risk. These attributes can be used to identify relationships between these indicators and an individual's risk. The use of this data in health care has been very limited until now. Its potential to improve accuracy in predictive modeling and reveal hidden or unknown trends is extremely high.

HCRM predictive modeling provides the most accurate and holistic view of health cost and risk in the industry all the way down to the individual. Now the socioeconomic health attributes can be used to complement and enhance the accuracy of existing predictive models or risk stratification efforts. HCRM is bringing this reliable and untapped resource of information.