SAS^® for Real World Evidence

SAS for Real World Evidence Features List

Data management

Ability to collect internal or external data from point-of-care systems, electronic health records, insurance claims, patient-reported outcomes, trusted third-party data providers and others.
Built-in capabilities for cleansing, standardizing, loading and integrating real-world data prior to using it.
Intuitive interface for profiling, integrating and moving data stored in Hadoop without having to code.
Process automation maps data to a common data model and refreshes cohorts and outputs as new data arrives.

Interactive drag-and-drop cohort creation for identifying research cohorts without coding.
Ability to run complex queries that go beyond simple subsetting to selecting criteria with multiple temporal relationships and Boolean logic.
Progressive patient counts and graphics for showing the effects of each inclusion/exclusion criterion on the patient population to determine study feasibility.
Reusable, editable cohort queries for improving productivity and efficiency.

Prebuilt analytical models, including predictive models for health costs, utilization and outcomes.
Analytics library of methodologies includes simple descriptive statistics, predictive analytics and machine learning methods.
Ability to use third-party analytics and visualization tools on defined cohorts.
Intuitive interface for including SAS or R programs and driving parameters.

Explore, visualize and report on real-world data sources to generate insights to support decisions on treatment regimens, gaps in care, reimbursement, formulary access or support clinical development decisions.
Predefined cohort characterization.
Ad hoc exploration capabilities.
Advanced visual analytics for understanding therapeutic areas, medical products or devices, and longitudinal effects of therapies on patients.

Point-and-click interface for navigating and exploring massive data sources with little or no lag time.
High-performance analytics run calculations on millions of rows of data in seconds, rather than minutes, hours or days.