5 Myths You Won't Need to Worry About When Adopting a Clinical Data Warehouse

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myths about healthcare data warehouseIf you’ve been thinking about implementing a clinical enterprise data warehouse (EDW), chances are you have a few questions about the possible problems you’ll encounter. It’s entirely possible that some of your fears are common myths; you’re not alone.

In this blog post, we’re going to be addressing some of the most common misconceptions associated with implementing an EDW in healthcare. Health Catalyst customers are proving these myths wrong, each and every day. We’ve been paying attention and would like to share them with you.

In reverse order, the top five myths about implementing a healthcare data warehouse are:

Misconception #5:

“I can’t provide broad access to my EDW because:

  • It will highlight underperformers and they will get mad at me
  • I know my source data aren’t perfect and I can’t explain data quality issues to my customers’ satisfaction.
  • Etc.”

On some level, every healthcare IT leader understands that for an EDW to achieve its maximum return on investment, it has to be used. But for some organizations, the thought of making data about care quality, affordability, efficiency, or patient experience is terrifying, conjuring up thoughts of career cul-de-sacs. It is perceived as safer to keep EDW data under lock and key than it is instill a data-driven culture and transform care.

So how do Health Catalyst customers address these concerns and provide broad, appropriate, scalable access to data? Through a very important concept in healthcare data warehousing: data stewardship. A “Data Steward,” sometimes called a Data Manager, is a subject matter expert who acts as a bridge between the EDW team and its customers. Some of the best Data Stewards are highly-regarded within their area of expertise, such as Finance or OB or Cardiovascular care.

On a day to day basis, Data Stewards are responsible for:

  • Approving/denying access to their section of the EDW
  • Reviewing EDW access logs for inappropriate queries
  • Answering subject area-specific questions from users of the EDW
  • Developing training strategies to ensure appropriate use of EDW data

You can read more about data stewardship in this article by Eric Just, VP of Technology.

Misconception #4:

“My users won’t need or want the ability to write SQL queries.”

Today’s business intelligence (BI) tools can create compelling data visualizations, and SQL is too difficult for the average data analyst to learn anyhow, right?

You would be surprised! I know I was when we instituted a SQL training program…and everyone loved it. If you use Excel and can grasp a Pivot Table, you can learn SQL.

Here’s why I feel pretty confident about that statement: In my first several months of a previous job as EDW manager for a large, not-for-profit health system, I heard loud and clear from many of our users that they were not interested in learning SQL. Having seen this before in my career, and seeing the transformation that eventually ensues when data analysts realize how much analytical power they have at their fingertips with an EDW and SQL-level access, my team didn’t force the issue.

But we quietly started doing two things:

  • We established free, monthly, beginner-friendly SQL training, taught by the Data Architects on our team.
  • We willingly provided SQL snippets and examples when analysts or report writers had a question that would be challenging to address in a BI tool, but might only take a 5-10 line SQL query.

The change over the last couple years for that company’s EDW user community was nothing short of incredible. As demand for data grew, users began to leverage our SQL snippet library to answer basic analytical questions. Then they began to modify the queries and wanted more SQL training to better understand why they worked.

We eventually developed an intermediate SQL course and loaded our SQL class schedule into the company-wide learning management system. Many data analysts benefited from two or three times through the course, which improved as our pedagogical skills improved – we were all learning as we went.

Some of what we learned included:

  • The most anti-SQL users eventually became the biggest users and supports of the power of SQL.
  • It doesn’t create chaos to have an active community of SQL user (see “Data Stewardship” above).
  • Users who were most facile with SQL became invaluable data heroes and opened up all kinds of career doors for themselves.

Misconception #3:

“I don’t need an EDW…my BI tool does everything I need.”

In short – today’s BI tools are incredible and do a lot more than they used to. But just as we can all relate to the adage “use the right tool for the job,” there are some really good reasons why we feel healthcare organizations need an enterprise data warehouse.

I addressed the why in earlier posts. Please see:

  • For the Healthcare CEO: Do we really need a healthcare enterprise data warehouse?
  • The IT Director

Misconception #2:

“EDWs are too expensive.”

They’re not. Learn more about the true cost of a healthcare EDW in Health Catalyst CEO Dan Burton’s article.

Misconceptions #1:

“EDWs take too long to implement.”

While it is true that traditional approaches to EDW development in healthcare have required timeframes in the several-years range, Health Catalyst uses an approach that greatly speeds implementation timelines.

Read the success story below to learn how Health Catalyst’s Late-Binding™ data warehouse enabled Indiana University Health to go live with their Cerner data warehouse in 90 days:

What other myths about healthcare data warehousing can we bust for you today?

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