Using AI to Identify High-Cost, Impactable Patients

Geneia's non-linear model accurately identifies patients' future costs at high-cost thresholds such as between $50,000 and $99,999 in health costs in the next 12 months. Our model requires less data to train, utilizes novel data sources and outperforms well-known commercial tools. The GDI Lab is working to determine whose cost can be most affected or, in other words, the impactable patients who are most likely to benefit from care management intervention. We know targeting only the riskiest patients means lost opportunities. For example, the chart below compares a risky patient with an impactable one, and shows the associated savings opportunity. High-cost and high-needs are not the same as highly impactable. As C. Annette DuBard, MD, MPH and Carlos T. Jackson, PhD, discussed in their paper, Active Redesign of a Medicaid Care Management Strategy for Greater Return on Investment: Predicting Impactability, "Targeting strategies that seek to identify patients based on high current or predicted costs or utilization are likely to identify large numbers of individuals whose healthcare needs will not be meaningfully altered by care management intervention." Their research with Community Care of North Carolina's Medicaid patient led to the creation of an impactability score.