Prepare to enter new disease management era
Prepare to enter new disease management era
Two pioneers say predictive models will reign
Many health care organizations rely on simple rules-based systems to identify patients who were at high risk yesterday and target them for disease management programs today. The problem is that these systems cannot identify the significant number of patients who will be at high risk tomorrow.
Predictive modeling does just that. "A predictive model uses whatever data you have available today — pharmaceutical, demographic, clinical, claims, health-risk appraisals — and uses those elements to perform a statistical analysis to prospectively identify those who will be at risk tomorrow," says Mark H.T. Ridinger, MD, president and chief medical officer of Axonal Health Solutions in Washington, DC.
Axonal received a research grant from the National Institutes of Health in Bethesda, MD, to develop and test its predictive model system, called HealthAugur, which can run 15 chronic disease models and produce stratified risk results.
"As we discovered, when you rely on claims data rules-based logic to identify at risk members, you find only a small minority of patients had prior hospitalizations for asthma," Ridinger explains. "When you simply identify this year’s high-risk asthmatics, you miss the vast majority of next year’s high-risk asthmatics. The real savings come if you can identify those asthmatics who are not yet high risk but will be in the future and plan appropriate asthma management interventions."
Advanced predictive models generally increase the number of at-risk patients who are prospectively identified by anywhere from 25% to 100% over conventional screening methods. What does that mean to a health plan in terms of cost savings and improved outcomes? To illustrate the differences between rules-based risk identification and predictive modeling, Ridinger gives the following example based on Axonal’s own research:
• A health plan with 200,000 covered lives has a population of 14,000 covered lives currently diagnosed with asthma.
• Of those 14,000 asthmatics, 700 to 1,400 (5% to 10% of the asthma population) is identified as high risk.
• The average cost of asthma management and treatment per covered life is $500.
• The average cost of asthma management and treatment per high-risk covered life is $10,000.
• Risk screening identifies 294 to 588 covered lives as currently high risk.
• Predictive modeling identifies 420 to 840 covered lives as high risk.
• Cost savings from correctly identifying high-risk patients is $8,500 per patient, or the $10,000 average cost of care for a high-risk covered life less the cost of disease management intervention.
• Cost savings from modeling is between 54 cents and $1.10 per covered life per year.
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