Linking AI Initiatives to Real-World Outcomes

Use Case

ACTUARIAL INFORMATICS: MEDICAL SCREENING & EARLY DETECTION

 
Client

Healthcare payer in collaboration with a healthcare provider, that serves patients in Philadelphia and the surrounding communities in Pennsylvania and southern New Jersey wanted to Identify eligible individuals who have not availed medical screening.

Problem

Medical screenings conducted for early detection of potential health disorders and diseases to ensure risk mitigation. Medical screening is the key to good health.

Methodology
  • Combination of Deep Learning based professional service and modularized AI components used according to organization’s cognitive maturity
  • Business transformation with smarter cognitive outcomes
  • Adding industry, business and customer insights to the value chain
  • Seamlessly integrate data across functions
Solution
  • An Actuarial Informatics solution created to enable the client to pinpoint eligible individuals who have not availed medical screening facilities
  • Machine Learning algorithms, created using SQL and Python are used to design clustering mechanisms
  • Business rules, adhering to HEDIS measures and guidelines incorporated into the algorithms
  • Clustering presentations created using D3 and reports are being generated in SSRS
Benefits:
  • 35% increased income due to the increase in the number of medical screenings, which are being paid for by the insurance provider
  • Client was able to generate income from Quality Performance Measure(QPM) incentives that are awarded on a PMPM (Per Member Per Month) basis
 

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