Transparency. It’s something we all want when it comes to governing bodies making decisions on our behalf and software companies using our personal data. We want to know how decisions are made and how things work behind the scenes so we know if we can trust the process. However in data and analytics, when it comes to transparency of our own work or the work of our team, we’re a little more hesitant. It’s not because we have something to hide, but we know with transparency comes more questions, more scrutiny, and more hassle.
But that extra hassle is an investment that pays off significantly long-term. Additional scrutiny in the form of more users evaluating the data surfaces more data quality and metric calculation issues. And the sooner we find those issues, the sooner we can fix them. Without transparency and the extra help validating data, data integrity issues will build and build and eventually catch up with us in a much more severe, and likely public, way.
So pull back the curtain to allow your customers to see the inner workings of your data warehouse and BI solutions, and as a result, you will create high-quality, trusted organizational assets. How can pulling back the curtain help build quality and trust? Well, because two of the biggest enemies of EDW improvement are obscurity and confusion, both of which are byproducts of a curtain that is tightly shut.
Obscurity
By Obscurity, I’m talking about the lack of awareness of what reports, dashboards, metrics, etc. exist in the organization and where to find them. If I’m a nursing unit director, and I’d like to see if a particular unit is improving its pain management scores, in most organizations my options for figuring out if something already exists that can help me are very limited. I might ask around to my peers to see if anyone knows about an existing report, or if I have a go-to IT or data analyst contact I might give him or her a call, otherwise, I’m going to submit a new report request and wait for someone to either point me in the direction of an existing report or put me in the queue for a new one. Even then, most request processes only cover a limited number of systems in the organization, so if the Patient Experience department has their own dashboard with pain management scores on it already, I may never find out about it and in a few weeks I might get a redundant report from the report development team.
Confusion
By Confusion, I’m talking about the lack of transparency of business logic that leads to an inability to determine how data elements and metrics are calculated, which inevitably leads to competing data and uncertainty about which data is right. As a leader or data analyst, I might have access to screens full of data, but if I have no way of finding out how it was determined which patients would be included in the diabetic population, for instance, I’m probably going to continue to do chart review because I can’t trust this list with no context behind it. And we’ve all been at meetings where we’ve witnessed conflicting metric results, like readmission rates, and neither party knows what definition is being used or how to find that information out very easily. Population, data element, and metric definition confusion are all big problems in nearly every organization in which we’ve worked.
Ok, so I’ve spent a lot of time describing the problem, but I haven’t left myself a lot of space to describe the solution. Fortunately, the solution to both the obscurity and confusion problems are easily said (if not so easily done). Here’s the answer: pull back the curtain! Expose the business logic of your populations, metrics, and data elements to all so they can know what metric they are dealing with and how it is calculated, or so they can search for “pain management” and find any reports, dashboards, or other assets that meet their need. Knowledge is power, and this is especially true in healthcare provider organizations where there are so very many metrics, so many disparate data systems, and so many groups calculating, validating, and being held responsible (via metrics) for performance.
Now in order to pull back the curtain, you are going to need tools to help you. Not massive, expensive tools, but a spreadsheet or document on a shared drive isn’t going to cut it. You need something web-based, easy-to-use, and with all the back-end connections (and yes, some people power too) to make sure your metric definitions are accurate and that all the reports, dashboards, and other objects are there for people to find.
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Learn more about how Compendium can help make sure your metric definitions are accurate.
