HSP’s Medimart™ data warehouse provides payers with rapid access to a unified repository of corporate data including claims, provider, utilization, care management and membership data. Medimart™ shapes this disparate information into a meaningful and responsive format. Flexible, powerful and easy-to-read reports and graphs can be used to provide the in-depth analysis that is essential to a payer’s business.
Data warehouses are optimized for speed of data analysis. Frequently, the data in these warehouses are denormalized via a dimension-based model. To speed data retrieval, warehouse data is often stored multiple times - in their most granular form and in summarized forms called aggregates. Warehouse data is gathered from the operational systems and held in the data warehouse even after the data has been purged from the operational systems.
In a dimensional approach, transaction data is partitioned into either “facts,” which are generally numeric transaction data, or “dimensions,” which are the reference information that gives context to the facts. For example, a claims transaction can be broken up into facts such as the number of claim lines and the price paid for the services, and into dimensions such as service date, patient name, procedure, provider and vendor. A key advantage of a dimensional approach is that the data warehouse is easier for the user to understand and to use. Also, the retrieval of data from the data warehouse tends to operate very quickly.