Regardless of what everyone thinks, the healthcare industry is in the infancy of â€œbig dataâ€. The concept isnâ€™t new, but we still have a long way to go, especially in pharmacy. I recall sitting at conferences years ago listening to sessions describing data collection and manipulation. The problem has been that data, especially that found in pharmacies is scattered across disparate systems without an effective method for connecting the dots. The adoption of electronic health records (EHRs) has made things better, but much of the data collected in an average acute care pharmacy is outside the EHRâ€™s reach. Â And to say that most pharmacies have their collective heads buriedÂ in the sand, would be putting it kindly.
Those on the outside often find it difficult to understand the sheer volume of data thatâ€™s produced in a pharmacy. Unfortunately, the data sources are mostly stored in disparate systems creating silos, which makes each system blind to the others. Is is possible to connect the systems and exchange data? Sure, but few if any are doing it.
Data sources inÂ pharmacies come from places like clinical interventions, inventory management, cost containment strategies, regulatory compliance, internal communications, and so on.
Take for example the simple goal of managing all the drugs used in an acute care pharmacy. Itâ€™s not uncommon for pharmacies to have several sources of data from various systems within the pharmacy:
- Room temperature items stored on shelves, carousels, or robots.
- Refrigerated and frozen items stored in refrigerators or freezers that may be tied to the room-temperature inventory management system, or maybe not. Refrigerated and frozen medications may use a completely different method such as an RFID-enabled cabinets tied to a secondary source of control.
- IV room inventory may be tracked, or more likely not tracked, once it leaves the â€œmain pharmacyâ€ area. It’s not uncommon for me to see IV room inventory treated as a location in which inventory is sent, i.e. no longer in inventory when it hits the IV room.
- Controlled substances, the bane of pharmacy productivity, is stored and managed separately from all other medications. Does it have to be? No necessarily, but the currently accepted practice is driven mainly by regulatory compliance and fear. Donâ€™t you think itâ€™s entirely possible to design a system that would more easily manage controlled substances? Of course! But that’s not the way we roll. We prefer the most difficult, least efficient system possible. Mission accomplished, because that’s exactly what we have.
- Management of medication kits, trays and transport boxes (trays). The amount of inventory stored in these trays is significant, and are often lost from pharmacy oversight upon reaching clinical areas. It’s amazing that medication trays are exactly the same as when I jumped into pharmacy practice nearly 20 years ago. It’s shocking just how poorly this area of pharmacy is managed. Some of my thoughts on the process can be found here.
Consider the amount of effort that goes into data collection for the soul purpose of regulatory compliance. Things like refrigerator and freezer temperatures, air flow and pressure differential in the cleanroom, documentation of blackbox warning drugs, and so on forever, create a mountain of information that is often collected on paper and stored in binders in some forgotten area of the pharmacy. Itâ€™s amazing in this is often considered best practice. I’m certain that much of this can be automated. Do other industries use such an antiquated system for data collection? I don’t know, but it shouldn’t be too difficult to find out.
Iâ€™ve mentioned only operational data to this point. What about clinical intervention data or financial information? The list goes on. Do pharmacy interventions really impact patient care in a positive way? I don’t mean in soft dollars, I mean in genuine, life altering ways? Possibly, at least in small studies. How about on a large scale? Don’t know. Can pharmacists actively improve pharmacy operations or the bottom dollar when engaged as part of the healthcare team? Don’t know.
Whatâ€™s worse is that the data collected from all areas of pharmacy is rarely, if ever, pulled out of silos and incorporated into other data sets. Whatâ€™s the value of that, you ask? Trends. Itâ€™s obvious to me that there are things within pharmacy data that we fail to see because the information is never compiled, stripped, joined, and analyzed. How big is the ripple effect of making a formulary change? Hard to say without looking at large groups of targeted data.
Itâ€™s staggering to think of what weâ€™re missing by not taking full advantage of the data being generated in a pharmacy each and every day. Not to mention what could be found by compiling data from several, or several thousand pharmacies at once. The value of collecting and digesting massive amounts of data from national, regional, and local pharmacy practices is infinite.
Imagine being able to build true data-driven practices in both the clinical and operational pharmacy activities. Is there value in documenting that a patient is taking a drug with a black box warning? Maybe, but we donâ€™t know. All we know is that some regulatory agency said we have to do it, so we do. But does it prevent anything? Who knows. Does drawing vancomycin troughs before the fourth dose improve outcomes, prevent toxicity, and decrease morbidity? Based on what I know, I think so. Has any of that ever been proven? Perhaps on a small scale, but nothing that Iâ€™m aware of that involves millions of data points. Then why do we do it? Because that’s the way it’s always been done. That’s the true definition of a non-data driven practice.
Is there a â€œbestâ€ way to handle sterile compounding? Is there a â€œbest practiceâ€ for monitoring patients on heparin? Iâ€™m not talking about guidelines based on expert opinion, here. What I want is for someone to compile data from thousands of pharmacies across the country and really take a hard look at what’s is being done in pharmacies.
Weâ€™re seeing some of this in practice areas like UCSFâ€™s precision medicine and many pharmacogenomics programs across the country. We should take their lead and apply those methods across the board. Data is power, and that power can be used to improve pharmacy practice. It seems to me that we have the ability, but thus far have failed to execute.
Someone call Google. They have a kind of data collection thingy, right?