Rethinking the Value (and cost) of data

I have had a number of conversations recently with some hospitals about storage requirements, and specifically where to put more gear as their data centers are bursting at the seams, or in some cases becoming structurally weakened because of floor loads. What I figured out pretty quickly is that there is an issue that is fairly ubiquitous to these organizations, but an issue that I believe spills over into any firm who stores data - all data is treated the same and is costing firms millions each year to treat all their data the same.

Here is one example:

A hospital is looking for data center space to grow their storage footprint into as they have tapped out every watt of space they have in the hospital. That's not even the real issue. The real issue is that because they have so many racks of gear, and heavy storage arrays on floors of the hospital with floor loads insufficient to support the weight, that the hospital is experiencing structural issues. Floors are sagging under the weight of all of the data being stored. Literally.

Many vendors they have talked to are simply telling them that's unfortunate but they need to buy more storage. However, the vendor won't get the sale unless his uncle is in the construction business and can structurally retrofit higher floor loads before the new arrays show up. So what does the hospital do?

Hospitals see patients, maintain facilities, manage compliance conformity, and administer services. Their IT guys set up storage arrays, networking equipment, and manage the applications that run the business. They are not in construction and they are not data center experts and yet are the go to guys to figure all of this out.
The solution that we began to discuss - and that I wanted to share - is that there is a fundamental change that MUST take place in how they think about data - storing it, managing it, accessing it, and realizing it's NOT all the same. The other thing that had to happen was to look at the way their business operates (no pun intended) and structure things in a way that are based on how their business runs, and not how their data flows today, but how it needs to flow based on their business.

Here is a specific example -

New patients create alot of new records. New paperwork, new insurance information, new MRI's, new test results, new billing codes, new invoices, etc.

Existing patients have this data on file and their data footprint changes with an office visit, an MRI, a perscription, and all of the associated charting that needs to happen to document the recent activity and results.

What are the commonalities of the two different kinds of patients? They create data around events - visits, procedures, tests. What are events tied to? A date. Can the date field be used to assess the freshness of data, and another date identifying the next event indicate the likelihood of accessing that data? Hmmmm. Interesting thought stream just started.

Where we got to was that whether or not the patient was new or existing, their events drove the need to access data. A new patient would likely need to be seen again shortly and would need to have their records accessible whenever. An existing patient who came in to have a sudden sports injury looked at would probably need to have their data file accessible since there would be consults, MRI's/X-rays, referrals, etc. taking place rather immediately.

A patient who was on a 'check in once a year' cycle, doesn't need their data accessed 363 days a year on average. They come in, get looked at, maybe a test is required (but we know what it is ahead of time) so why is the 'active' patient's data sitting with a 'maintenance' patient's data in the same facility, withe the same cost, and with the same SLA (service level agreement) or DAA - data access agreement? Why would you pay for 363 days of something you don't need? I equate it to paying for a rental car in Seattle for 365 days, while I am only in Seattle two days a year - why would I do that?

The point here is that yes, they do need more storage. They can't put it where they usually do - in their data center - and need to find someplace else to expand to. But before they just go out and buy new arrays, new cabinets, new servers, and lease new space, they MUST look at things in a new way so that not only are they solving the immediate issue -'we need more storage' they are solving the fundamental issue - all data is NOT the same and does not need to be managed the same, or cost the same.

Thoughts?