Collibra helps Envision Healthcare and its patients tackle insurance claim issues

Within Envision, data governance is formalizing the processes and roles that are already in place to ensure trust in data. “One of the first things we did was interview data citizens across all of our functional groups and we uncovered 50 different data entry and collection systems,” revealed Schmidt. “In radiology for instance, there were five different data delivery methods including PDFs and spreadsheets.”

Envision looked at several data governance solutions but ultimately chose Collibra. The company used the Collibra Rapid Start Implementation Service to enable best-practice deployment. “In choosing and rolling out Collibra, we learned to let the vendor help you,” recalled Schmidt. “Many pay lip service about making you successful; Collibra proved it. The company advised and guided us through the implementation process. There were times we worried that the Collibra team was the ‘tail wagging the dog’, but we leaned in and let them guide us to do the things we might not have known to do.”

Collibra encouraged Envision to conduct a maturity assessment, re-look at use cases, and develop a success and adoption plan. “We learned so much more about our own use cases even though we thought we had already defined them,” added Schmidt. “Every person we have dealt with at Collibra has been a special advocate for us.”

The data governance program at Envision uses Collibra Data Intelligence Platform running on AWS and they are using the Data Quality & Observability, Data Catalog, Data Governance and Data Lineage capabilities. Collibra is integrated with several complementary applications such as Microsoft SQL Server and Tableau.

Before deploying a solution, Envision invested time in preparing and setting expectations for the business. “We did not want to fly in with an IT app,” explained Schmidt. “I spent two months with numerous teams, listening to their pain points. Then another two months with technical stakeholders prepping data and two more weeks with data owners. But they did not want anyone touching their data. My advice is, engage with data owners up front and emphasize that data governance is about metadata, not the data itself.”

Once Collibra was up and running, Envision used Data Catalog and Data Quality & Observability to ingest data warehouse documentation, understand the data and develop an up-to-date business glossary. This enables users to search, find and interpret data. For instance, a clinician looking at a Tableau dashboard uses Collibra to research term definitions, find data owners and map lineage.

The data that Envision gathers includes administrative data such as HR, financial, credentials, scheduling, payroll and clinical. To manage quality of care, the company has 51 KPIs incorporated into Collibra which measure aspects such as treatment outcomes, success of stroke treatments, or number of sepsis cases by clinician, site or shift.

Data governance at Envision does not fix or clean up the data, it is there to highlight problems and issues. For example, there is a 72-hour-returns KPI which tracks whether a patient needs to come back to a clinic within 72 hours. Data governance looks for consistency across all ER facilities and signals if there are missing or incorrect data fields or attributes. A clinic with an unusually high number of 72-hour-returns rate might require investigation.

Another threat to revenue is being able to identify when a clinician is off plan. For every clinical procedure, the clinician needs the right credentials and an active insurance plan, otherwise Envision cannot bill for related treatments. “These instances are perfect use cases for data governance,” explained Schmidt. “We can look at large data sets like 14 million hospital visits, and spot records where clinicians appear not to have an insurance plan, see why they don’t have a plan, and rectify the issue so we can bill for treatments.”

Doing this manually used to take up to six weeks, by which time Envision could have stated expected income incorrectly. With Collibra, this is done in a day.

Because of the complexity of clinician work patterns like swapping shifts with higher- or lower-paid colleagues and late-shift bonuses, there is a lot of catch-up pay. In addition, Envision has grown by acquisition and has gained a multitude of different and complex contracts with different shift types, patients seen and quality levels. This is integrated and managed by Collibra, so clinicians are paid accurately and on time.

Since the data governance program went live seven months ago, Schmidt has seen significant engagement from staff with approximately 900 people accessing Collibra, 60 data stewards appointed and bi-monthly data steward meetings attracting up to 30 attendees.

Schmidt offered some advice for people considering or starting a data governance journey. “I read about one definition of data governance that made me laugh. It said it was the execution and enforcement of governance over data,” said Schmidt. “Our data governance journey is about listening to people and finding their pain points, showing them they are already doing what we want and formalizing processes that are already in place. That is one of the reasons why we have been so successful.