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Case Study 10.19.2021

Optimizing Operations for On-Demand Healthcare

Trexin helped design a new analytics platform for a leading provider of software for urgent care centers.

Optimizing Operations for Healthcare

Business Driver

Our Client, a market-leading software company specializing in electronic medical record and practice management software for urgent care clinics, decided that a new business intelligence (BI) and analytics platform should be incorporated into their next generation of digital technology to provide enhanced capabilities and business insights for their customers’ on-demand healthcare practices. With time-to-market advantages in mind, the CFO asked Trexin to bridge some developmental resource gaps by leading the component-level design of the data model.

Approach

Clarifying the analytics platform would have a Tableau-based user interface driven by a Snowflake database deployed in Amazon Web Services, Trexin adopted a Kimball approach focusing on the data model design for three subject-oriented data marts: patient data, claims data, and billing data. For each mart, Trexin led a detailed analysis of all in-scope data domains and source tables. This analysis defined business requirements in terms of key performance indicators (KPIs); defined non-functional requirements for data security to support data segregation in a shared service model; and defined the basis for an enterprise glossary that described the names and abbreviations for the data attributes to be modeled. Trexin then designed the data model to meet the specified requirements and created detailed source-to-target data mappings. This process included analysis of the data; creation of a conceptual, logical, and physical data model; identification and modeling of slowly changing, conformed, degenerated, role-playing, and static dimensions, including date and time dimensional granularity; identification of transactional versus aggregate facts; and design of composite and surrogate keys for fact tables. Trexin then integrated the dimensional data model into the broader BI model, updated data dictionaries, and published data definition language (DDL) statements for deployment, repeating this entire process for each of the three data marts.

Results

The finalized dimensional data models were deployed into Snowflake and integrated with Tableau, empowering a full-service analytics and business intelligence platform for our Client’s urgent care customers to use to optimize their on-demand healthcare business.

Tagged in: Analytics, Digital Transformation, Growth & Acceleration, Healthcare & Life Sciences, Optimized Operations, Technology