List of SAS Episode Analytics Customers
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Since 2010, our global team of researchers has been studying SAS Episode Analytics customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased SAS Episode Analytics for Analytics and BI from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using SAS Episode Analytics for Analytics and BI include: Envision Healthcare, a United States based Healthcare organisation with 55000 employees and revenues of $16.00 billion, Geneia, a United States based Professional Services organisation with 200 employees and revenues of $100.0 million, Arizona Care Network LLC, a United States based Healthcare organisation with 65 employees and revenues of $17.0 million and many others.
Contact us if you need a completed and verified list of companies using SAS Episode Analytics, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the Analytics and BI software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Arizona Care Network LLC | Healthcare | 65 | $17M | United States | SAS Institute | SAS Episode Analytics | Analytics and BI | 2016 | n/a |
In 2016 Arizona Care Network LLC initiated implementation of SAS Episode Analytics in the Analytics and BI category to standardize encounter-level clinical data. The project began with a formal scope to implement CDISC standards alongside the SAS implementation of the Observational Medical Outcomes Partnership OMOP standard for encounter data, aligning clinical records to standardized data models for downstream analysis.
Implementation work focused on configuring SAS Episode Analytics modules for episode construction, cohort definition, and standardized encounter mapping. The configuration included data model normalization, ETL pipelines to translate raw encounter records into OMOP-conformant structures, and CDISC-aligned metadata tagging to support clinical reporting and regulatory-ready datasets.
Operational integration centered on ingesting encounter datasets from the organization clinical sources into the SAS Episode Analytics framework, enabling clinical analytics and population health workflows to consume OMOP-standardized episodes. The deployment covered clinical analytics and care management functions, with data feeds routed into reporting and visualization processes configured inside SAS Episode Analytics.
Governance work established CDISC and OMOP mapping rules, validation checkpoints, and a staged rollout plan to onboard departments to the new episode analytics capability. The program emphasized controlled data standardization and repeatable mapping processes to ensure consistent encounter normalization across the network.
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Envision Healthcare | Healthcare | 55000 | $16.0B | United States | SAS Institute | SAS Episode Analytics | Analytics and BI | 2016 | n/a |
In 2016, Envision Healthcare's Evolution Health implemented SAS Episode Analytics. The deployment positioned SAS Episode Analytics as an Analytics and BI solution for episode-based cost analysis and coordinated care assessment, enabling clinicians and care managers to model episodes such as joint replacement and chronic disease treatment.
SAS Episode Analytics was configured to establish diagnosis-specific baselines and to support clinician-driven adjustments for severity and case complexity. Functional capabilities implemented include advanced episode definitions, episode attribution logic to differentiate avoidable complications from typical services, and configurable modeling to assess the full cost of coordinating care across service types.
The implementation emphasized operational use by clinicians and care coordination teams to examine relevant services across the entire continuum of care, including pre-admission, inpatient, post-discharge, rehab, home health and long term care. The solution acts as an Analytics and BI layer that surfaces episode-level cost and service patterns to clinical stakeholders and care management workflows.
Governance and workflow change centered on clinician interaction with episode models, with clinicians starting from a baseline diagnosis model and adjusting parameters to reflect patient severity and complexity, embedding model tuning into care pathway reviews. Evolution Health expected that advanced episode definitions and the use of SAS Episode Analytics would improve care and patient outcomes by enabling separation of avoidable complications from routine services.
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Geneia | Professional Services | 200 | $100M | United States | SAS Institute | SAS Episode Analytics | Analytics and BI | 2015 | n/a |
In 2015, Geneia implemented SAS Episode Analytics. The deployment focused on Analytics and BI to provide episode-based clinical and cost analytics for accountable care organizations, reflecting the collaboration between Geneia and SAS to improve patient health.
SAS Episode Analytics was configured to support episode construction, cohort analytics, cost and utilization analysis, quality measurement, risk stratification, and interactive reporting dashboards. Configuration emphasized reusable episode definitions and attribution logic, automated analytics pipelines for recurring reporting, and role-based dashboards to support population health and care management workflows.
Operational scope centered on ACO operations and care management teams, with the solution embedded into clinical governance and performance monitoring processes. Governance established centralized analytics stewardship and iterative configuration cycles to align episode definitions with ACO performance frameworks, while ongoing collaboration between Geneia and SAS supported refinement of analytics and reporting to improve patient health.
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