The following is both an insightful and entertaining client email to Mainspring from Matthew Bruns, Business Systems Analyst for Hartford Healthcare Corporation, in response to asking him for a high-level overview of his expectations for accessing a library database of medical device manufacturers and models.
Like any card-carrying geek, I abhor anything that resembles actual work. So our conversation today is about an especially onerous task that I am stuck with, and the best way to find someone else to do it for me.
One day our descedents might very well take a tour at some museum of natural history, and wandering into the wing housing the exhibit on early 21st century humans, they might observe interactive images of office workers hunched over glowing desktops with open windows of email and Excel. They’ll likely gaze in the same kind of wonderment as we do of Neanderthals wielding primitive stone tools. We can’t take that guided tour at the Smithsonian just yet. While we’ve been heralding the death of spreadsheets and email for years and will continue to do so, the truth of the matter is they’re not going anywhere anytime soon. Sometimes we just need to see them for the tools that they are.
I was visiting a new client recently, discussing a project we were doing at their hospital to clean up their equipment data. While looking at some of the data in their legacy system, we saw many inconsistencies and mistakes that had managed to creep into the database through the day-to-day activities of the users over the years. For example, they had several device types, manufacturers and models describing a single piece of equipment, which was causing inventory reports on that equipment to be incorrect. With multiple naming conventions for one specific piece of equipment, it was difficult to manage recalls and alerts, because the database had to be manually screened to find everything affected. It was even more concerning that the inconsistencies in the data caused problems in preventative maintenance scheduling for the equipment.
We live in an information age where reliable data is everything. Informed decision making with technology and the data behind it is not just a smart choice, but a way of life for most of us. Better and faster information is available at our fingertips, and it’s making our lives easier. Technology plays a major role in delivering that information, but we often forget that in most cases, technology relies significantly on other humans to provide that information in the first place.
Data is a commodity. We collect and store data. Heck, we even call them server farms. While silos are good for farmers, they are bad for data management — time killing, bottom-line-eroding bad. For a hospital, data silos mean departments are operating on assumptions, and there’s no room for assumptions in healthcare when patient safety and billions of dollars are at stake. Breaking down data is a crucial step in increasing visibility across hospital operations and saving much needed capital.
There’s an old saying that says numbers don’t lie. I say they’re capable of telling half-truths. Gather up all the numbers in one place and you start getting some straight talk out of them. Gather up only a few and now (knowingly or unknowing) you’re making some “educated” guesses. It’s the basic fundamentals of card games like Poker and Black Jack—trying to figure out where the ace and where the deuce is. That’s fine and dandy if hospitals were into riverboat gambling; not so much when it comes to capital planning.
There's a point near the end of Mad Men's epic television run where, after seven Emmy award-winning seasons, a computer finally makes its appearance at the advertising agency of Don Draper and company. The episode is titled "The Monolith" (a veiled reference to "2001: A Space Odyssey") and in it we see an IBM 360 mainframe being wheeled in piece by piece, ultimately to take up an entire break room at the office. The requisite "ribbon cutting" announcement heralding the computer's arrival is met with a mix of optimism, skepticism and even fear.
Evaluating Computerized Maintenance Management Systems (CMMS) can be a challenging process, especially when you're looking for healthcare specialization and more than basic break-fix capabilities. In TechNation magazine's article titled "Roundtable: CMMS Software", industry leaders recommend some key questions to ask when you start evaluating CMMS software.
Here are some of our favorites:
As I continue to consult with clients and prospects, there is an all too common theme amongst them. While most are very focused on evidence-based data to improve clinical outcomes, far fewer seem to be using evidence-based data to drive operational improvements such as making sure clean, patient ready, bedside mobile medical equipment is available in the right place at the right time.
Thanks to the Affordable Care Act, healthcare leaders must continue to find ways to reduce the cost of care delivery. While many eyes are focused on readmission and/or length of stay reductions tied to reimbursements (or the lack there of), the 'hidden side' of their healthcare delivery system, hospital operations, can also yield substantial cost reductions without having to reinvent the wheel.
As much as I loved being a Biomedical Engineer and Safety Officer in a former life, I could still spend the next day ranting about the daily headaches biomeds face. But for whatever reason, regulation update annoyances stick out to me like a sore thumb. With so many regulatory agencies infiltrating our brains with a never-ending stream of confusing jargon, it can seem impossible to stay on top of every update. This led me to ask myself, how can Biomedical Engineers keep up with all of the changing regulations without causing themselves constant headaches?