Case Study

Population Health Analytics Engine

Orthogonal worked with our customer, a population health management subsidiary of a large Health Insurer, to rearchitect and develop a population health analytics engine that aggregates and analyzes clinical patient information derived from claims, lab and EMR data against established clinical best practices to optimize quality of care, population health and wellness.

The system reviews the entire patient record and compares the information against thousands of clinical rule sets derived from evidence-based sources. When an opportunity for better care has been determined, the system alerts members and their physicians about possible care gaps and other inconsistencies.

The system’s architecture is built on an aggregation of approved clinical rules, HIPAA-covered PHI, legacy claims and predictive algorithms that can be leveraged for simple population health analytics services, as well as for direct disease management and early intervention programs.


The original system was not architected to handle the data volume and complexity of the algorithms (millions of covered lives, thousands of health monitored events and thousands of clinical rules.)

As a result, system management was becoming increasingly challenging and processing speed was becoming unacceptably slow. At the same time, the system needed to scale dramatically, both in terms of covered lives and clinical rules.


Orthogonal architected and developed a new system using a five tier architecture, that includes ETL processing of EMR, claims and lab data, operational data stores and data warehouses, a clinical rules engine, enterprise web services, java and .net applications and web and mobile interfaces.


The system was able to scale to 40 million covered lives, 1200+ health monitored events and 9000+ clinical rules. Analytics processing time was reduced from 2 weeks to sub 5 seconds, and system management became significantly easier.

Since then, the software has helped clients monitor 64 million individuals, achieve 8.1 million health improvement and save an estimated $8.4 Billion.