Not too long ago I had a pain in my shoulder. I’ve had stiff necks that sometimes traveled a bit down the arm, the kind that goes away if you stretch it enough, or at least gives you confidence that it will go away with time. This was an unusual pain, gradually worsening during the day and preventing me from getting comfortable when I laid down to go to bed. I didn’t think it would go away.
I finally gave in and told my wife that I think I needed to get it checked out. By now it was 10pm, and the emergency room was our only option. I’ve spent years writing about healthcare and how data is used in the industry, but other than during my annual physical, I never really saw it in action. Here’s a little bit of what I learned about the healthcare industry, and data’s role in it, from my night at the ER.
Triage
One of the most popular data points I’ve written about in the past five years has been the burnout rates of medical professionals. It was one of the first things I thought about when I saw the number of people already in the waiting room after I checked in. Almost immediately my name was called and I knew it was too good to be true—I was not being examined, just triaged.
The triage nurse was very nice to me. She knew I was in pain and was very patient with me as I tried to describe something that for me was very difficult to put into words. I didn’t really know what had happened to my shoulder or how to relate the pain I was feeling. I thought about how she had to go through this with at least dozens of patients, offering all of them, ideally, the same amount of grace. All of this was happening at a time of night that I know I’m not the best version of myself, and yet every interaction was friendly.
Later, as I sat and waited my turn, I witnessed other instances that would try the patience of even the most disciplined doctors and nurses. More than one person complained about their wait time, while another could be heard demanding to go home. One patient forced a security guard to literally spring into action – jumping over the registration desk—in order to calm a situation.
My turn
I thought about a number of quality metrics when it was finally my turn to be examined. My emergency room wait time was about an hour and a half, and I spent another hour being examined and then released. How long a patient waits before being seen is something hospitals keep track of, as well as LWBS—whether a patient “left without being seen.” I admit there was a moment when I weighed whether I should just go home and see what happens with my shoulder instead of waiting longer.
The first thing the physician assistant did after speaking to me was order an x-ray. That process took five minutes, and I saw the doctor shortly afterwards. He immediately knew what was wrong—I had biceps tendinitis in my left shoulder. The pain would get worse for the next few days, he said, and then start to feel better. That’s exactly what happened. I’m glad I didn’t leave before I was seen—I probably would have come back when the pain worsened.
Thinking about analytics
While my shoulder was a pretty open and shut case, I thought many times throughout the night about all of the data I was contributing to the hospital’s emergency department. Mine was a pretty quick case to resolve, so I was helping the overall metrics as far as wait times were concerned once I saw a doctor. I observed many more data points throughout my visit, from the number of beds being used in the emergency room (all of them—including the beds lining the hallways, one of which I was assigned, in order to treat more patients while all the rooms were filled) to other elements like staffing and a “How Did We Do?” patient satisfaction survey a week or so later.
Of course, the only thing that matters to a patient is their health. In a best-case scenario, all of the technology and data is working towards producing the best possible outcome for any patient. In order to get those types of results, hospitals need the best possible analytics solution. The right solution provides data to drive decisions that improve patient care while helping the hospital operate in the most efficient way, without interfering with the way patients are treated.
My ER visit quickly made it clear to me why emergency rooms are the focus of so many television shows and movies. While my shoulder injury might not have been a major plot point, my relatively brief stay overlapped with many more dramatic situations unfolding at the same time. The data and analytics part of hospital work also might not make it into the dramatic portrayals, but make no mistake: they are a big part of what allows everything else to unfold in an optimal way.
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