It's easy to think of a typical patient. But the fact is, there is no such thing. For example, heart disease doesn't always affect middle-age men more than women. That's why it's difficult to get meaningful profiles on patients and community members with cluster segmentation methods based on group statistics and neighborhood demographics.
Predictive segmentation changes all of that with two systems that use sophisticated mathematical techniques, healthcare variables and disease states to actually predict health outcomes by scoring the individuals in your database.
- The Consumer Healthcare Utilization Index (CHUI)SM offers a score from 0 - 999 to indicate an individual's propensity to use healthcare services as defined by the major diagnostic categories (MDC) and specific diseases within the ICD-9 and diagnostic related groups (DRG). CHUI is ideal for non-patients.
- The patent-pending Patient Disease Index (PDI)SM is a co-morbidity segmentation system that leverages CHUI to predict the likelihood of individuals who have or have had certain diseases to develop other health problems. PDI is ideal for your patients.
In addition to applying CHUI and PDI scoring results for more focused intervention, disease management and campaign efforts, predictive segmentation is proven to be financially more beneficial than traditional segmentation methods.
If CHUI were used to target the top 5 percent of individuals in a market of 400,000 individuals (with 2,140 inpatient cardiology encounters), the cardiology charge results would be approximately $4 million for demographic or cluster methods of market segmentation and nearly double that or about $7.7 million with CHUI. PDI results would be almost double those gained by using CHUI and four times as effective as cluster code or demographic segmentation.
Fabric of NetworksTM
Fabric of Networks is a diversified mathematical technique that increases CHUISM prediction capabilities 3-10 percent. The technology, introduced in 2006, works by creating a pool of diversified neural networks that collectively score an individual. The pool can outperform a single network because any weakness in the single network is supplemented by others within the pool. This technology provides superior selection methodology to identify the most appropriate individuals for personalized communication.
Your patients are anything but typical. Predictive segmentation gives you more insight into each individual for more focused, efficient and valuable programs.
To learn more, read our predictive segmentation white paper, predictive segmentation information sheet and our latest predictive segmentation press release.
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