DOS Marts™

DOS Marts Data Models are foundational, intermediate-binding data models that draw from multiple healthcare source systems to aggregate data into domain-specific marts. Raw data is transformed into deep data by augmenting with business logic, algorithms, industry standard terminology, and code sets. Commonly used values are normalized, grouped, flagged, and served up for rapid and easy consumption by query and visualization application. DOS marts are both upgradeable and extensible. Profiling tools are included for data validation and table and column metadata are fully documented with bindings, dependencies, and diagrams.

DOS Mart List: https://products.healthcatalyst.com/table-of-contents/dos-platform/fabric-data-services/dos-marts/?alttemplate=HCDOSMarts3 

DOS Marts are domain-specific, created and maintained by subject-matter experts in each healthcare product area.

The problem

Healthcare systems face diminishing returns on analytical investment. Why? Because analytical teams waste time and talent on SQL rework — writing the same multi-source queries again and again to answer common questions (e.g., Which encounters were inpatient encounters?). These efforts are not scalable or transferrable across the team. And the answers generated may not be reliable considering duplicate patient records and differences in terminologies across source systems.

Current solutions include vendor and homegrown data modelling. These have a narrow focus and do not scale well outside a limited set of use cases. Some models are locked down and cannot be customized to fit a healthcare system’s particular use cases, so they go unused, resulting in wasted time and resources.

Our approach

DOS Marts aggregate and model data based on the specific use cases of your domain areas with out-of-the-box business logic, algorithms, and terminology normalization to eliminate the majority of SQL rework. Each domain-specific model groups and flags your data to make it more quickly consumable while preserving extensibility via the addition of custom columns. 

Benefits and features

• Raise ROI and stakeholder satisfaction – High-quality, validated data models speed your time to actionable insights and improvements in every domain area.
• Scale your analytics resources –Source-taming algorithms pull your analysts up out of multi-source SQL rework to focus on high-level advanced business analytics.
• Get insights in hours instead of weeks (or months) –Aggregate, map, group, and flag data into the right formats for fast consumption. You can build visualization applications or query the marts directly up to 90% faster than with lower-level data interactions.
• Monitor and report with the most current data – DOS Marts load incrementally to serve up the latest data in a fraction of the time of full refreshes.
• Govern your data with included tools – Automated interactive documentation with every DOS Mart shows bindings, dependencies, and dataflow. Profiling tools validate marts to ensure the highest quality data and valid insights.
• Extend and customize – Add definitions and columns to meet your unique needs, while keeping the core mart upgradeable.

Use cases

• A not-for-profit healthcare system is facing payer pressure to close gaps in care. Clinicians need actionable information about clinical performance in relation to patient outcomes but their EHR and legacy data model is difficult for analysts to wade through, resulting in slow response times. Using DOS Marts, analysts are able to deploy visualization dashboards and get insights in as little as 1 week, saving months of the typical time it takes to implement improvements.
• A CIO for a multi-regional health system seeks to improve ROI and stakeholder satisfaction with analytic performance. She needs to demonstrate value for dollars invested in an analytics team that's understaffed and overwhelmed by the challenges they face. She decides to add DOS Marts to their existing analytical repertoire. Data analysts discover they can use the DOS Marts as foundational building blocks that level-up their starting point for each new project. They no longer have to delve into complex multi-source SQL queries and can focus on advanced business analytics. Job satisfaction and engagement improve, increasing ROI across the system.