Nurse helping an elderly person.

Care Management

Healthier members, through data-driven decisions.

We predict avoidable:

  • Ambulance.

    ER Visits

  • Hospital Bed.


  • Stethoscope

    Behavioral Health Admissions

  • Medical chart.


Proactive. Not reactive.

Decision Point leverages machine learning to identify patterns and trends that drive member-level risk predictions, informing curated engagement strategies.

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Archery target with a caduceuson on the bullseye.

Pinpoint the right members.

We can identify the 5% of members who account for 50% of admissions. Casting a small, yet accurate net enables our clients to focus their resources on the members that will have the greatest impact on plan performance.

  • 1.8

    average ER visits
    avoided per member

  • 16:1

    average ROI annually

  • 23%

    average annual reduction
    in avoidable admissions

Members are complex.

Clinical data tells only part of the story.

Plans have a difficult time understanding how their members move throughout the world. Traditional healthcare data sources are necessary to build an informed engagement strategy but only provide a glimpse into the factors that are truly impacting a member’s well-being and health system engagement. We enrich plan data with consumer and census data sets to build deep, layered member profiles that allow our clients to better understand their members as people.


  • lives with others

  • is a home owner

  • is a pet owner

  • lives 10 miles from PCP

  • is a college grad


A couple sitting in a couch.


  • lives alone

  • rents an apartment

  • has behavioral health issues

  • is unengaged with his doctor


A person sleeping in a couch.
OPUS member profile.


An actionable member summary that supercharges engagement.

OurOpus Member Profile delivers an at-a-glance view of a member’s historical experiences and predicted future behavior, enabling health plans to rapidly understand and act upon critical intelligence.

See it in action