I recently reviewed a summary article entitled How are other systems breaking down data silos? 35 leaders share. What I found most interesting were the expressed notions of why data silos exist and what these leaders are doing about them. A lot (but not all) of the responses focused on infrastructure issues to get data to be consistent and shared more broadly. Several spoke of cultural changes being necessary to overcome those silos.
This caused me to think about our practice in health-system pharmacy, how we wind up with our own data silos, and how we get past them (or do not).
Pharmacy is, perhaps, unique in the acute care world in that we tend to operate on a variety of automated systems, each of which may look at the world in quite diverse ways. While an increasing amount of our data is winding up inside electronic medical record (EMR) systems, much of it still exists in technology that operates in parallel to those EMR systems, and to each other.
Further, even when systems are well-integrated, the way we wind up installing and using those systems often contributes to data that others might find useful being buried in inaccessible places or not being captured at all. The following questions relate to data to which we have legitimate access, and whose use is unconstrained by law, regulation, or professional standards.
- Are you data sparing or data greedy? In my experience, the time to have data is not when you discover you need it; by then you have failed to capture it for your use. You may be able to capture it moving forward, but that likely won’t meet an immediate need. When making decisions about configuration and use of automated systems, I am a fan of being data greedy. When given the choice, do you opt to capture more data or limit what you capture to what you think you currently need?
- Do you see your data as an asset to be managed and maintained? I often encounter systems whose maintenance has languished. Part of this comes from our tendency to treat our automation installations as events rather than as ongoing responsibilities. Some of this is likely the tyranny of the urgent, but it amazes me how little effort sometimes goes into keeping data accurate, current,and consistent, even when there are tools available for that purpose.
- When you install technology, how much do you consider use cases for the data the technology generates? It has been my experience that we focus a lot of attention on getting data into our systems, but extraordinarily little attention on getting it back out. As the demand for analytical systems and artificial intelligence grows, we are likely to find that our early implementation decisions get in the way of back-end analysis of that data.
- Does your staff understand how automation workflow and configuration decisions affect the quality and availability of data? In my experience, our staff tend to treat enterprise automation systems much as they treat their personal automation. They use it “my way.” The result is that those systems capture less usable data than they could simply because some users choose to use those systems in ways that hide that data value.
One of my favorite examples of this involves tracking the time and effort spent on managing medication expiration in automated dispensing cabinets. While most of these systems have functions to identify transactions related to managing expiration dating, I have seen several facilities in which the individuals performing that function have chosen to handle them differently, burying that data indecipherably in inventory transactions. I am certain that those who choose this path do so because it seems more efficient to them. In making that decision, however, they artificially constrain the usability of that data.
There are several reasons to use a system the way it was designed to be used; a key reason is that such use results in data that can be used analytically to measure and improve operational performance. Pharmacy leaders could therefore take the opportunity to educate their staff both on how systems are intended to be used and why (what data we will derive at what benefit when the system is used correctly).
So, in my opinion, our systems exist in silos in large measure because we do not implement and manage our automated systems as data assets that could, and should, contribute to the larger ecosystem of health system data that drives both our operations and our strategy.
The thoughts of this blog are my own, and not necessarily those of my employer or of ASHP.
Dennis A. Tribble, PharmD, FASHP
Ormond Beach, FL
datdoc@aol.com