Clincal Information Life Cycle Management
By David Yeager
Vol. 13 No. 4 P. 6
As data storage capabilities continue to increase and storage costs decrease, healthcare organizations are saving ever-growing volumes of medical imaging data. There are reasons for this trend, such as potential research applications and perceived affordability, but what’s often lacking is a long-term storage and migration plan. Although clinical information storage is often considered to be increasingly convenient and inexpensive, will it still seem that way five to 10 years down the road when it has to be migrated to a new archive?
Some might argue that because storage capacities have continued to double roughly every two years for more than a half century, they will do so indefinitely, with a commensurate drop in cost. However, that could be a very expensive wager. If the growth in storage capacity slows significantly, which would almost certainly increase its cost, huge data repositories will become a huge liability. And, even if costs don’t rise, migrating clinical information that is growing exponentially will cost money.
“Right now, it is not a crisis. And until it becomes a crisis in the institution, when they have to start spending massive money to keep moving all this stuff, it’s a hidden cost that nobody’s paying attention to,” says John S. Koller, president of KAI Consulting. “The mindset is out there [that] disk is cheap and, until that changes or the volumes of data get so huge that [no matter] how cheap disk and storage are there’s still going to be a significant cost with that migration, nobody’s going to pay attention.”
To a certain extent, enterprise archive and middleware vendors have been able to address concerns about these growing volumes by providing larger repositories and more migration options, but Koller believes clinical information life cycle management will need to be part of any effective long-term strategy. Although some enterprise archives have at least limited management tools, they are largely unused.
Life cycle management is a simple concept: The institution sets rules that determine how long each type of data is kept and when those files should be purged. However, its practice is significantly more complex. When it is done, institutions usually do it manually rather than through policy rules. What it boils down to, Koller says, is determining the business value of the clinical information to the institution, which is also a complex calculation because the value of that data changes over time. He adds that deciding when to make the evaluation is as important as deciding how to evaluate it.
“All data has a business value. It may be very high; it may be in the midrange; it may be low or nonexistent,” Koller says. “But [institutions] have to look at the business value of this data because it’s used for delivery of healthcare, it’s used for research, it’s used for training. Each one of those components has a contribution to the business value, and then they have to figure out whether the cost of collecting, storing, migrating, and protecting the data, for whatever period of time, is appropriate for the business value.”
Of course, there is some clinical information that must be kept. Each state has its own requirements for general record retention, usually five to seven years, and pediatric records are typically kept much longer. Mammography and oncology records need to be kept for the life of the patient. Once the regulatory requirements have been fulfilled, though, the institution needs to think about what the data are worth.
Although there is no consensus about how to calculate that value, Koller says there are some helpful guiding principles. After regulatory requirements have been met, the value of the clinical information to the institution and its patients needs to be weighed against the risk and cost of keeping it. When looking at the value of a particular file, one consideration is whether the patient is still coming to the institution. If a significant amount of time has elapsed since the patient was last there, is there a reason to keep the data? Some cases may have been flagged by a physician for training purposes. Others may be involved or have the potential to become involved in a legal process.
The value decisions that are made vary by institution. Because academic medical centers place a high value on education, training, and research—and typically have significant resources at their disposal—they can generally justify keeping clinical information longer. The future possibilities of conducting very large longitudinal studies with anonymized data have been a driving force in many institutions’ decision to save everything. On the other hand, small community hospitals, which are generally on a tight budget, most likely have little need for clinical information that they’re not legally bound to keep, especially if it’s not being used for patient care. Ultimately, institutions need to determine if the benefits are worth the cost.
Think Now, Pay Less Later
“What’s going to justify spending money to keep that data that’s continually migrated? Because there is a cost,” says Koller. “Technology ages, technology breaks, technology changes, so there’s a cost of moving that forward forever or for whatever period of time it’s kept.”
The fact is, though, many institutions are not doing business analysis on their clinical information. Because of the time and expense involved with such an undertaking, many are simply buying more storage as it’s needed, although some are beginning to look at cloud options that will manage the data for them. But if they’re not looking ahead, they may be costing themselves money in the long run. What they need to be doing, Koller says, is figuring out whether the money they’re spending today is going to make it easier for them to manage their clinical information over the next five to 10 years.
“It will hit one day, and the smart institutions will be thinking about it now, especially if they’re going to be changing PACS vendors or they’re going to be making some sort of capital investment related to that data,” Koller says. “If they keep doing the same thing, all they’ve done is postpone it. The pile of data gets larger and larger, and the problem is going to be greater next time than if they start thinking about it now.”
— David Yeager is a freelance writer and editor based in Royersford, Pennsylvania.