We've known the value of healthcare data for decades. So, why do we still struggle to integrate it?
When is the last time you had to sell someone on the value of data? Maybe never. The importance of data for decision-making is one thing everyone usually agrees on. Many view data as the most valuable resource in the world.
Your clinicians know the value of data. They know it as much as you the people in operations, finance, accounting, marketing, IT, and your strategic leaders. This development is hardly new—not in general and certainly not in healthcare. Health Level Seven (HL7) was founded more than 30 years ago with the specific intent of providing a standard for exchanging healthcare data.
For something that’s been universally accepted for so long, by now you’d think we’d be good at integrating it. Ironically, the value of data is often the biggest impediment to integrating it for analytics. Your software providers – whether EMR/EHR, practice management, scheduling, lab, etc. – also know the importance of data to their users.
This is where the trouble often begins. Purchasing and implementing a Lab Information System? You can be sure it will have reporting. Who would think of buying an EMR with no reporting module? The thought of billing software without built-in reporting would be laughable.
Those systems are (hopefully) great at processing transactions. That’s what they do, of course. But they create tons of data during the process. Do they provide reports on and analysis of that data? Well, that’s a different question. Transaction-processing software vendors know they have to check that box – but often, they are just doing just that…checking the box. Reporting is probably not their strength.
There are exceptions (and they get better every day) but many users feel their best option is to try and extract the data as best they can and put that data into a spreadsheet. Even for the exceptions – those that do provide good data visualization – you’ll eventually need to integrate data from multiple sources.
All of this leads us to what can be a counterintuitive conclusion: The quality of data visualization for transaction-processing software should usually not be an important consideration in its selection. Of far greater importance is how well that tool makes its raw data available for extract.
The purpose of your data mart/data lake/data warehouse is to provide information for decision support. That information comes from data that’s extracted from transaction systems. If your EMR or billing application is difficult to query (at a detailed level) into a database, then it will be harder and more expensive to get to the data-driven insights.
Next time you are selecting a transaction-processing software vendor, ask them to hustle through the reporting demo. What you really want to know: How open is their application to direct data extract access? We’re talking about all of your data.
Saxony Healthcare is committed to helping our clients do more with their data and technology to improve outcomes, reduce waste and inefficiencies, and drive performance. We tackle issues related to data access and quality, process automation, software selection, denials management, revenue cycle management, and more. Reach out to us via our website or LinkedIn to chat about how we can leverage technology to turn your data into action, streamline processes and procedures, and optimize the way you do business.