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The Objective, n=1 Data You Need to Optimize Care

Lifestyle Factors: Lifestyle indicators are widely used by consumer marketing companies to target messaging and engage individuals.  They have rarely been used in health care but are increasingly important to compete in today’s competitive landscape.  Working with this data requires specialized skills that the team at AXL brings.


SDOH Factors: AXL applies its AI algorithms to match household and individual data to determine and objectively measure SDOH challenges being faced.  This data is currently either not available or can only be gathered through time-consuming interviews or less accurate, population-level data.  AXL data is at the n=1 level.


Clinical Risks: AXL combines its lifestyle and disposition data with clinical data from claims and EHRs to identify current and potential future clinical risks.

What Makes AXL Different

Data Correlation: AXL aggregates, matches, and statistically reconciles data from multiple sources to derive valid, trustworthy insights.

Domain Expertise: AXL’s team has the relevant data science and health informatics expertise to reconcile data from multiple sources and apply them to healthcare.


Proprietary Algorithms: The AXL intelligence are the result of 4 person-years of research; applying specialized knowledge brought by AXL’s PhD-level data science team; incorporating vast input from peer-reviewed clinical and technical sources.  It also reflects learning from the many failed attempts along the way.  AXL has received a provisional patent for this work.

Applicability: The risk scores AXL provides synthesize data into actionable measures for making timely, real-world decisions and tracking progress in healthcare.

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