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Predictive and actionable analytics

Identifying patients mostly likely to benefit from clinical intervention

CCNC’s approach to identifying the most “impactable” patients has broken new ground in care management targeting. While management of high-cost/high-needs patients is a common strategy to reduce health care costs, CCNC has been able to answer a much more compelling question: How can we identify the patients who are most likely to benefit from care management intervention? 

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CCNC has continued to evolve its management targeting strategies at CCNC in North Carolina's statewide Medicaid population, culminating in the development of an  Impactability ScoreTM  that uses administrative data to predict achievable savings. CCNC estimated intervention effects in a historical cohort of patients receiving complex care management versus a control population to estimate total cost savings at an individual level. The savings was then used to determine the predictive contribution of a multitude of demographic, clinical, and utilization characteristics.

CCNC found that utilization patterns unexplained by disease burden proved to be far more important predictors of impactability than any given diagnosis or event, disease profile, or overall costs of care, and that social determinants often played a significant role in patient needs.Community-based CCNC care managers engage with identified patients, many with multiple chronic conditions, to address barriers that could impact their healthcare outcomes.

For each patient, an individualized care plan is developed  with his or her assigned care manager. These are the patients CCNC care managers can really help – not just the riskiest or most expensive. By focusing on individual care plans, quality of care is improved while avoidable hospital admissions and readmissions are reduced.

Compared to other targeting strategies, impactability-based targeting provides two to three times the return on investment. Savings per patient can be as high as $6,000 annually.

CCNC's approach was recently highlighted in an article published by Population Health Management, a peer reviewed medical journal. To read the article in its entirety, please click on the downloadable file at right.  You may also be interested in CCNC's Data Briefs (see link at left), articles that provide detailed information on population health, data use and care management.