GuidingSigns™ Analytics

GuidingSigns™ is a web-based clinical decision support system that transforms data into actionable insight for health care payers and providers. GuidingSigns combines predictive risk scoring, stratification and grouping with gaps-in-care analytics to identify evidence-based health improvement opportunities across hundreds of clinical care and behavioral health indicators.

 

Built-In CDPS Risk Model

Embedded within GuidingSigns is CDPS (Chronic Illness and Disability Payment System), a predictive risk model developed by the University of California San Diego using Medicaid data from 44 states. CDPS analyzes diagnostic and pharmacy data to identify and group populations into more than 60 risk categories, and is available exclusively for commercial use within GuidingCare.

 

Fine-Tune Risk Assignment For Your Population

GuidingSigns can incorporate additional sources of risk based on availability of data. For example, social determinants such as income, education, housing, literacy and access to support services can be derived from health risk assessment tools that are available or can be added to the system. Each source of risk can be “weighted” to fine-tune its impact on the overall risk score for a population.

 

Seamlessly Link Analytics with Care Plans and Interventions

GuidingSigns includes extensive integration points with the GuidingCare™ care management platform. Analytics output from GuidingSigns - including risk scores, condition-based risk groupings, gaps in care and corresponding service and education interventions - directly populate relevant GuidingCare fields and automate patient-specific care plans.

 

Align Care Management Strategies with Resource and Program Requirements

Clients can modify risk scoring, weighting and more based on program requirements and available resources to ensure that the right strategy for care management is deployed to the right number of members.

GuidingSigns™ can help put your highest-risk members on a path to better health. Let us show you how.