Lay the foundation for successful analytics

Too often, source data must conform to some standard extract, which burdens the data provider, takes time, and causes relationship strain. Or analytics vendors insist on owning the integration step, a "black box" approach that reduces trust in the process and potentially limits use cases. Or internal teams write code in an unsupported way, which takes time and creates additional technical maintenance burden. 

For Ursa Studio users, “healthcare data integration” is not merely reformatting source fields; instead, it is the full preparation of an enriched enterprise reporting environment. With a unified toolkit for accessing source tables, accommodating the variation in expected concepts, and wrangling the ones unique to that source, users can glide through no-code interfaces to review individual cases and iteratively develop accurate logic. The output is a comprehensive data model that serves as the high-integrity foundation for all downstream analytic building blocks.


How you benefit

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Say "yes to the question, "Can you use my healthcare data that comes in <X> format?" when working with new external partners or industry sources


Deploy a battery of industry-leading validation rules and algorithms to surface data issues, accelerating the investigation of new sources and maintenance of ongoing feeds


Access the richness of Ursa Health's Reference Library to contextualize your healthcare data and create robust building-block tables that fuel high-powered analytics

Start off with a rich tool set

Ursa Studio simplifies and automates some of the more onerous aspects of ingesting raw data, ensuring you have the visibility you need into the process at every step. 

For example:

Create, submit, share, and import modules from one instance of Ursa Studio to another.

Save ELTs and automatically trigger them to run daily, weekly, or monthly.

Give any user-generated source a unique identifier, and easily determine which sources are used in which ELTs.

Define and document API calls to enable seamless integration with third-party tooling.

Quickly diagnose issues

Developing and maturing our our own data model means that we are intimately familiar with what it needs to work. We've built very detailed and specific validation rules throughout the data journey to ensure the data is well formed and standardized — no need to worry about building this yourself.

That system of checks and balances begins with data ingestion and integration. Once your data has populated the Core Data Model, Ursa Studio fires a detailed series of validations to help assess whether the myriad concepts that comprise the data model have been structured correctly. For example, Ursa Studio elegantly handles patient mastering, creating a single ID across all data to eliminate duplication.

Issues that may not be readily apparent surface, allowing you to address them before they impact later stages. And every time you transform data, these validations rerun. 

Enrich your sources with healthcare reference data

A standard component of the platform, the Ursa Health Reference Library is a meticulously curated synthesis of international code sets infused with best-in-class third-party resources and proprietary intelligence. These look-up tables are vital ingredients for enriching healthcare's data ontologies. No need to research, acquire additional licenses, or perform any new set-up — we handle the painstaking compilation and maintenance.

So instead of working with an indecipherable 11-digit NDC pharmacy code, for example, you're viewing drug names, the way each maps to a therapeutic class of drugs, average pricing, and more. Add descriptive fields to raw data code fields, create custom value sets based on your internal business logic, interpret complex data sets, and more. 



Minimize resources and improve accuracy with integration accelerators

In addition to the rich software feature set of Ursa Studio, organizations have the option of deploying an array of Ursa Health Integration Modules to expedite the process of working with specific types of healthcare data. Modules bundle up specific mapping and interpretation logic for selected data extracts.

For data sources that are less standardized — for example, a health plan claims data package — the modules provide broad guard rails and validity detection tools to support the user. For data sources that are more standardized — for example, packages from CMS or from an EMR database — the modules essentially automate a large portion of the integration work.

Below are examples from growing list of Ursa Health Integration Modules.




Standard CMS flat files available to ACO REACH program participants, including Claim and Claim Line Feed (CCLF) files, Weekly Reduction files, and Alignment files

Generic claims data

Any package of tabular payor claims data, including medical and pharmacy claim data in transactional or final action format, member and membership period data, and provider data

Generic EMR data

Any package of tabular clinical data from an EMR or similar system, with concepts including encounters, problem lists, scheduled appointments, orders, and lab results

Canvas EMR data

Key concepts from the Canvas EMR, including notes, encounters, scheduled appointments, problem lists, orders, surveys, observations, and lab results

Humana Service Fund data

Data from the Humana Service Fund claims package, including medical and pharmacy claims, members and membership periods, and provider data

athenahealth EMR data

Key concepts from the athenahealth DataView EMR, including notes, encounters, scheduled appointments, problem lists, orders, surveys, observations, and lab results

Want to talk?

We’d love to hear about your ideas for innovating in your organization and see if we can help ease you past your pain points.