Data Lake / Data Warehouse Modernization · Document Processing · Real-time Analytics
However, all of this became increasingly difficult to facilitate as the organization continued to scale their offerings and grow their member base, which came along with an ever-growing mix of structured, unstructured and semi-structured data from multiple systems of record.
Reported impact
SCAN Health Plan achieved measurable business impact on Databricks, including 3.6% Decrease in voluntary disenrollment for members targeted for earlier primary care physician reassignment; 4.59% Reduction in voluntary disenrollment during annual enrollment.
Despite it being a current obstacle, SCAN’s unstructured data (e.g., call center notes, medical charts, PDF medical documents) could ultimately serve as the major unlock for the organization as it expands into the clinical realm. One of the reasons why the not-for-profit Medicare Advantage plan was already developing a natural language processing (NLP) pipeline throughout the various peaks of the COVID-19 pandemic — and continues to do so — was to uncover member behavioral patterns and detect recurring themes in member service interactions. Unfortunately, the NLP model couldn’t reach the next level of development until data access and the pipeline were improved first.
Unstructured documents and reference data lands in Databricks and is transformed into curated datasets stored in Delta Lake under Unity Catalog governance before being served through Databricks SQL
3.6% Decrease in voluntary disenrollment for members targeted for earlier primary care physician reassignment
4.59% Reduction in voluntary disenrollment during annual enrollment
SCAN Health Plan is one of the nation’s largest not-for-profit Medicare Advantage health plans.
SCAN began to build out their data science efforts to help unify unstructured and structured data from sources including electronic medical records (EMR), claims submissions and member engagement data.
SCAN looked to Databricks to quickly extract valuable data insights to facilitate preventive healthcare.
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
The official fact sheet lists "Employees 1,727."
Related
Google Cloud Sample Archived · Apr 13, 2026 Interclinica Interclínica utilized Looker’s conversational analytics API to create "SofIA," an AI agent that eliminates "cognitive friction" by allowing leaders to access complex healthcare KPIs through natural language. This… Achieved 100% data-driven adoption among the pilot group BigQuery · Cloud Composer · Looker 
Databricks Sample Aug 14, 2025 EY-Parthenon They needed a partner — not just a platform — capable of scaling AI-powered workflows, unifying fragmented data sources and embedding intelligence securely and compliantly across global engagements. 30%–50% Efficiency gains, accelerating client decision-making and unlocking new opportunities Agent Bricks · Databricks SQL · Delta Lake Databricks Sample Nov 3, 2025 Children's National Hospital Yet, Children’s National struggled with a fractured data architecture that created barriers to basic reporting, timely insights and advanced research. “Historically, Children’s National had fractured data architectures… 2,160x Faster model training resulting in better pediatric care AI/BI · Agent Bricks · Delta Lake 