Predict | Metabolic Syndrome

Identify metabolic syndrome and promote early detection.

Almost one-third of all U.S. adults—approximately 80 million people—meet the criteria for metabolic syndrome (MetS), a clustering of risk factors that often leads to chronic diseases. And yet, public awareness of MetS is alarmingly low. This is especially problematic since it can be mitigated and prevented, improving outcomes and lowering the $220 billion associated annual healthcare costs.

BUILT FOR HEALTHCARE

Ingest, normalize, and blend data
from dozens of health data sources.

Electronic Health Records
Unstructured Clinical Notes
e-Prescribing Data
Vital Signs
Remote Monitoring Data
Medical Claims
Rx Claims
ADT Records
Lab Test Results
Social Needs Assessments
Social Determinants of Health
Operations & Services

Risk patient will develop metabolic syndrome

HIGH RISK

Patient ID

Gender

Age

Risk Score Percentile

583889012

Male

42

97

Impact on risk

Contributing factor

Value

+26%

Increase in Fasting Blood Glucose Levels (mg/dL)

80 to 105

+18%

BMI Level

29

+14%

Rise in Blood Pressure (mmHg)

130/90 to 150/100

+10%

Decline in Sleep Quality (episodes / week)

2 to 5

AI INFORMS ACTION

Pinpoint high-risk individuals and surface actionable risk factors.

ClosedLoop generates explainable predictions using thousands of auto-generated, clinically relevant contributing factors.

Provide

Provide patient self-management education

Promote

Promote continuity of care and increase assessment frequency

Improve

Improve adherence to exercise and diet regimes

EXPLORE MORE USE CASES

Readmissions

Payers

Providers

Predict readmission risk and improve transition planning.

Serious Fall-Related Injuries

Digital Health

Payers

Providers

Reduce fall-related injuries and improve functional support.

Drug Safety

Payers

Providers

Anticipate and avoid adverse drug reactions.

Make AI/ML a core element of your care strategy.

Get in touch today to see the ClosedLoop platform in action.