How it was.
It was a simpler time for physicians not so long ago. But was “simpler” just blissful ignorance? The only inputs that were incorporated into our treatment plans were ones that were made available to us. Images, labs, vitals…if something wasn’t placed in the hospital chart, we didn’t know about it. There was no “real-time” diagnostic information flow. The concept of data-driven prediction of risk was nonexistent. Normal-but-trending labs? Time-series comparison of outside and current imaging studies? Medication risks? None of these words were even in our vocabulary.
How it is.
Now, the pendulum has swung to a state of data overload, and too much of a good thing isn’t always…useable? We are bombarded with data from ventilators, vitals systems, imaging systems, lab systems, medication administration systems, and of course – the EHR! These systems provide a continuous stream of patient data – many of them in real-time. But buried deep inside these vats of data are a handful of key elements necessary for clinical decision making.
Why is it so hard to leverage the data to find meaningful, actionable information? Let’s start by looking at the workflow involved in patient care. The EHR remains the “Queen Bee” of clinician workflow tools. Data from many disparate sources eventually make their way into the EHR.
But to use the EHR, you must log in, open the patient’s chart, and wade through various screens to find the data you know you want. What about the data you didn’t know you needed? Things like urine output shifts in a patient placed on a nephrotoxic drug prior to your assuming care for him?
And let’s talk about EHR alerts. Alerts aren’t really “alerts” if you don’t know about them unless you actively open the patient’s EHR record first. That’s like a carbon monoxide detector that requires you to log in before notifying you of deadly levels of carbon monoxide caused by the lint ball clogging your clothes dryer vent.
And how do you access all the real-time patient data living outside of the EHR? One would have to log into dozens of different data sources, at the same time, and somehow place them side-by-side to create some semblance of data aggregation. Any manual attempts to make sense of this data might only reveal a fraction of the patient story hidden inside.
How it should be.
We’ve come a long way from searching for paper charts, hunting down x-rays, and calling the laboratory for results. But streams of electronic, disparate data that don’t provide actionable insights aren’t sufficient, either. Whats missing is connectivity. When every minute counts (literally, a 60-minute delay in treatment increases sepsis death by 8%), these data must be meaningfully aggregated and presented, in real-time, in one place.
Think of your car’s dashboard. In one glance, you know how much gas you have left, how fast you’re driving, and more importantly - how likely you are to have an issue with tire pressure or engine function. The car takes data from various components, interprets it, and gives you a visually optimized, actionable summary. Armed with this information, you know exactly what to do to prevent risk.
Are we there yet?
How close are we to achieving this level of data efficiency inside the hospital? Close…
Health tech companies, established and new, are pairing up to shift the state of inpatient care from “how it is” to “how it should be.” Imagine a single console that not only provides visually simplified, real-time data like medication graphs and lab trends, but it generates actionable recommendations for immediate intervention. That same console might also contain telehealth features to enable remote care of populations of patients - even across multiple facilities.
Imagine one user-interface that eliminates the need to log in to various systems or rely on stale EHR data. One source of meaningful information – provided at the right time for the right level of care. That’s how it should be. Stay tuned. We’re almost there…