IDC has projected that healthcare data will grow faster than any other sector by 2025 due to “advancements in healthcare analytics, increasing frequency and resolution of MRIs, and other image and video-related data being captured in today’s advanced modes of medical care.”

In fact, healthcare data will top 2.3 zettabytes by 2020, according to another IDC report, with medical imaging and other unstructured data accounting for much of that number.

Historically, enterprise imaging has been a catalyst for advancements in health IT and the same is true today.  Imaging is front and center as we develop and leverage augmented intelligence algorithms, which promise to allow our scarce clinical resources to focus on the sickest patients first. The future of medicine is truly exciting and effectively managing imaging, and other data, is key.  Are you ready for the future?

The promise of data revolutionizing healthcare is great, but preparation is key.  Just because a healthcare organization stores data and has analytics tools to run on the data, doesn’t mean it will achieve the outcomes expected and needed.  In fact, many organizations are fraught with failed data analytics projects because the integrity of the data is assumed and not thoughtfully planned for. 

Today, in the face of a tsunami of imaging data, when I ask clients about image lifecycle management (ILM), many times the response is “we don’t need ILM, we don’t delete images.”  It shocks me that organizations think of ILM only in terms of data deletion.

For years, we’ve ignored the need for meaningful image lifecycle management (ILM) by leaning on the mantra “storage is cheap, we don’t need to think about deleting images.” ILM is about effectively managing imaging data—not just deleting data.  Effectively leveraging ILM ensures that the information is available at the time it is needed, delivered as quickly (or slowly) as needed and managed in the most cost-effective ways as the use cases for the data change.  To have a good ILM strategy, you must consider not only the expected data lifecycle, but the data characteristics required to enable the successful management of data. 

With IT budgets shrinking, rate of data growing, and our reliance on that data ever increasing, the time to develop robust data management strategies, including ILM, is now.  The rest of this blog series will focus on the key tenets for an overall data management strategy and why it’s so important to the future of our healthcare IT revolution.  

Developing a holistic enterprise imaging strategy with appropriate data governance, including image lifecycle management, will help your organization safely and securely access, manage and maintain medical image assets. The next post in this series will cover the steps to developing an efficient data lifecycle strategy.

Learn more about our enterprise imaging solutions by visiting us at HIMSS 2019 (booth 969) or by contacting us.

Kim Garriott is Principal Consultant of Healthcare Strategies for Logicalis, responsible for helping clients develop and implement clinically focused IT strategies that center on leveraging business value and providing an optimized patient experience.