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3M™ Clinical Risk Grouping (CRG) Software

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3M™ Clinical Risk Grouping (CRG) Software can be used both to predict future health care utilization and cost and explain past health care utilization and cost. 3M CRGs are a population classification system that uses inpatient and ambulatory diagnosis and procedure codes, pharmaceutical data and functional health status to assign each individual to a single, severity-adjusted group.

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A patient-centric and clinical model that enables change

A patient-centric and clinical model that enables change

3M CRGs are patient-centric, focusing on the total burden of illness rather than one disease or service, and use a categorical approach to patient classification that provides clinicians with actionable data. Solventum’s approach contrasts sharply with statistical models that yield regression-based risk scores that have little clinical meaning.

Suitable for all populations

Suitable for all populations

3M CRGs were developed for use in all populations, including pediatrics. Particular attention was paid to the most complex and expensive patients across the full spectrum of age and insurance status. Among other uses, 3M CRGs are commonly used in measuring the illness burden of medically complex children.

Flexible

Flexible

3M CRGs are available in both prospective and retrospective models, useful for understanding both past utilization and predicting future utilization. Solventum provides multiple levels of 3M CRG aggregation to fit the required level of detail. And, unlike regression-based models, the 3M CRG categorical approach allows the clinical model to remain stable while relative weights vary depending on the population, covered benefits and payer policies.

Risk adjustment for important health outcomes

Risk adjustment for important health outcomes

3M CRGs are closely integrated with the Potentially Preventable Admission (PPA), Potentially Preventable Emergency Department Visit (PPV) and Potentially Preventable Service (PPS) methodologies. PPAs, PPVs, and PPSs are increasingly popular ways to measure and manage potentially preventable events to improve population health.

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