In the healthcare technology space, ask someone what “archive” means, and depending on who’s using the term and what their intended use case may be, you’ll get a different answer from nearly everyone. The very definition of the word “archive” is fluid – and as a result, exists on a continuum.
After your organization implements a new patient accounting system, your staff still have to work down the AR from your legacy system. If you must continue to operate (and pay for) the legacy system you’ve just replaced to do so, you’re taking a significant hit to the return on your new investment. It’s a recurring hit, too, as it can take years to zero out your books. And, by keeping legacy applications that have outlived vendor support, you’re increasing your organization’s exposure to risk.
The terms data conversion and data migration are often used interchangeably. And, while this is incorrect, there are plenty of blogs and articles out there explaining the difference between converting data (changing it from one format to another) and migrating data (permanently moving data from one location to another) that will set you straight.
Rather than add to the conversation about their definitions, we’re going to talk about why it’s not enough to talk about data conversion or data migration without also considering data archiving.
Everyday there are 2.5 quintillion (yes, that number has 17 zeros in it!) bytes of data created. More than 90% of all the data that exists in the world was created in the last two years. And the pace of data creation only continues to accelerate. As good data stewards, we must take ownership of the data we create to harness it to solve problems and make systems more efficient.
It starts simply enough: Your organization meticulously matches platform capabilities to your organization’s needs and decides on a new EMR. You set the project schedule, took the system live and even optimized it to maximize user efficiency. Everything is perfect…okay, as perfect as any large system implementation can go…But, then, it happens. You remember that throughout all the planning, capability matching and optimizing, you forgot to think about your legacy data.
With the vast amount of data your organization produces daily, properly caring for this data is critical when implementing information-based care. Data Stewardship is a sub domain, a discipline if you will, within information governance that is predicated on ensuring the accessibility of data assets. In short, successful Data Stewardship will prevent your organization from being data-rich, but information-poor.