SAS^® Health Solutions

SAS Health Solutions Features List

Health & Life Sciences solutions

Empower providers, public health and life sciences organizations to drive trusted health innovations and accelerate time to value with SAS Health Solutions.
Unlock explainable insights faster to make confident decisions at every moment.
End-to-end solutions for health data integration, management, automation and analytics.
Connect to internal or external data from point-of-care systems, electronic health records, insurance claims, patient-reported outcomes, health devices and trusted third-party data providers, as well as non-health data sources.
Provide machine learning, artificial intelligence and visualization capabilities for addressing pertinent industry-relevant business challenges.

Easily ingest data from industry-standard formats, including Fast Healthcare Interoperability Resources, into a common data model.
Establishes secure access to various systems, data sources and applications.
Automates incremental data load for faster decision making, reporting and analytics.

Integrates health and non-health data sources, and prepares data for analytics. Manages data and analytic model lineage.
Explore, visualize and report insights from real world data sources.
Identify treatment pathways, gaps in care and barriers to reimbursement.
Gain support for formulary development, market access and clinical development.
Understand unmet needs in therapeutic areas, medical products or devices, and longitudinal effects of therapies on patients.
Access embedded advanced analytics and apply transparent AI and machine learning predictions with repeatable explanations of data, models and predictions that complement descriptive analytics and help you with confident decision-making, such as the anticipation of member/patient needs.
Creates transparent reports and unlocks analytic insights faster, such as disease prevalence within a population, patient outcomes or potentially avoidable care.
Includes techniques such as clustering, decision trees, linear regression, logistic regression, generalized linear models, generalized additive models and nonparametric logistic regressions.
Built-in bias monitoring and transparent explanations of data, models and predictions complement descriptive analytics and drive confident decision making, such as the anticipation of member/patient needs.

All users across your health organizations can access analytic insights via our low-code/no-code, graphic user interface.
Enables all users to participate and have analytic insights at their fingertips.

Enrich existing data sources by combining event output with traditional data sources for gaining insights.
Create customized episode definitions and associations for rapid time to value.
Generate new insights, such as provider attribution, financial implications of potentially avoidable complications, outlier studies and risk-adjusted cost comparisons based on trusted analytics.
Build retrospective and prospective bundled payments to identify savings, to identify financial and clinical risk, and to expose potentially avoidable complications.
Identify areas of improvement in patient care coordination.

Cloud-native and cloud-agnostic with complete portability across on-premises, hybrid or multicloud environments.
Enables you to get the best models into production quickly or deploy them into the decision/workflow engine.
Lets you register models in a centralized repository for version control and simplified compliance processes.
Easily integrate teams and technology across the analytics life cycle, enabling all types of SAS and open-source users to collaborate.
Lets you refresh cohorts and analytic outputs based on data refreshed through process automation and common data models.