Predictive Analytics:
Accurate and Actionable

In any population, be it a community, a health plan, an employer, an educational institution, even a faith community, there are those with undetected, uncontrolled, or misdiagnosed chronic conditions. Not only do they represent a guaranteed financial risk, with COVID-19, their risk of catastrophic health events, even death, is many times higher.

Just as important as identifying those with chronic conditions, predicting the spread of COVID-19 is critical to the community health.

Decode Health uses unique data structuring and modeling techniques to identify and track disease risk. The result is actionable insights for health systems, payers, and municipalities to mitigate COVID-19 spread and reduce adverse events and high cost events for chronic disease populations.

How We Do It

Tackling chronic disease and COVID-19 quickly and accurately requires the investigative minds of immunologists AND the analytical speed, scale and efficiency of machine learning.
Decode Health is one of the few companies in the world that has both. That’s what sets us apart.

RECEIVE

Client sends healthcare claims and other structured data

ENRICH

Decode layers its proprietary data + social determinants of health

ANALYZE

Decode trains, tests, and optimizes models to uncover patterns and score populations

DELIVER

Decode identifies at-risk patients and delivers actionable information to care teams

ACT

Care teams engage at-risk patients to provide education and impact treatment plans

The Bottom Line

Example: Autoimmune Disease Cost Savings Analysis

$5K

Average total healthcare
spend PMPY

$15K – $125K

Range of autoimmune
spend PMPY

20+%

Savings potential
on annual autoimmune spend

3-5X

Projected ROI
using Decode’s platform

Find Your Chronic
Disease Problem

Sample Impact from Autoimmune Disease

  • Up to 16% of your managed population has one of the diseases and conditions we detect and monitor.
  • They cost your plans and employers millions.
  • Savings from correcting misdiagnosis is significant in the first year.
  • 25% of claims are categorized with ill-defined R diagnosis codes and some of that population will likely have an autoimmune or chronic  disease.
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