Predict | Suspect HCCs

Identify suspect HCCs and improve accuracy.

Risk adjustment is quietly becoming an economic cornerstone in healthcare, and the Hierarchical Condition Category (HCC) is at its core. Because HCCs determine payments, they influence an organization’s economic viability, available resources, and care delivery capacity, which means accurate and complete diagnosis coding is becoming an economic and clinical imperative.

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

Likely undocumented condition for CHF

HIGH RISK

Patient ID

Gender

Age

Risk Score Percentile

143958712

Male

71

97

Impact on risk

Contributing factor

Value

+29%

Decline in LV Ejection Fraction

0.45 to 0.35

+14%

Dyspnea on Exertion

June 14, 2020

+10%

Procedure for Electrocardiogram

June 14, 2020

+10%

e-Rx for Beta Blockers

June 14, 2020

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.

Identify

Identify and address gaps in coding to capture annual capitation payments

Assess

Assess documentation determinations to automatically improve accuracy

Refine

Refine diagnosis identification continuously

EXPLORE MORE USE CASES

Length of Stay

Providers

Reduce length of stay and improve outcomes.

Chronic Obstructive Pulmonary Disease

Digital Health

Payers

Providers

Identify COPD and promote early diagnosis.

Operational Efficiency

Payers

Providers

Predict utilization and optimize scheduling.

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

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