Decisions in medicine are supposed to rest on concrete observations and hard evidence.
Often, hard evidence does not exist or when it does, it isn’t used. Why is this?
Concrete observations, too, are increasingly missed as we stare at computer screens longer and patients less. Yet we persist. Why?
This is our reality now, our evolving medical world.
But if we stop and think about it, medicine, by definition, is a world of technological faults, systemic frailties, and human inadequacies. We are convinced we know how a patient dies, for instance, thanks to the wonders of unprecedented imaging capabilities but stand slack jawed when an all-too-underperformed autopsy discloses a surprise cause of death that was completely missed by all.
And our answer to these inadequacies? Stop doing autopsies. Even though autopsies have consistently shown that one in four deaths occurs from an unexpected outcome or complication of care.
Why did we stop doing them? Let me count the reasons: we are human, you see.
Increasingly we are foregoing clinical judgment and intuition in favor of big data to make decisions. We construct 70-page appropriate use criteria for ICD documents that cover (really) just a few special clinical circumstances for patients, as if the authors ever really know a patient’s clinical circumstance. Ask yourself how good we are at predicting the day a person will take their last breath? Like the weather, life is impossible to predict even when you have a billion data points or more.
Big data and its certainty are our hottest trend in medicine and academics right now. We know why this is: we love technology. It is rational. It is understandable. It is linear. We want, desperately, to understand and compartmentalize our human condition, to minimize its variability, so we can ration our resources logically. But rather than acknowledging the limitation of such an approach, we forge ahead and create logic from dissociated databases with incomplete or empty data fields based on highly-selected patient populations to make our points.
Outliers are considered nothing more than acceptable loss rations. We manipulate and massage the incomplete or erroneous data using statistics to make our points seem more valid. Then, like the azithromycin folly, we extrapolate that data and transmit our firmly held beliefs through government agencies to the masses. We feel good about our myopic analyses and are happy our academic salary was secured for another day. In return, the importance of medical judgment, experience, and intuition to medicine are cast aside by our fervent belief that trials, databases, and data manipulation are always free from bias and the influence of greed.
But in the face of medical uncertainty, what other than judgment and intuition does a physician have — or a patient have, for that matter? The real patient that sits before us demands an answer where, more likely than not, no real answer exists. Real concrete clinical challenges are rarely represented in a clinical trial or computer database. So we listen. We observe. We review data. Perhaps we get a second opinion. Patient judgment, life experiences, and intuitions are factored, too. Then we decide, together. Medical judgment and intuition are like that: not all luck, not all logic.
But now with big data, the new requirement for wellness and fitness is going to be for patients to keep proper symptoms that stay within the lines. Symptoms and findings must fit new rubrics. If they don’t, your caregiver won’t know how to treat you, the computer won’t know how to treat you, and the rubric won’t know how to treat you.
Who are you to say your symptoms are unique? Who are you to deserve a special look? In the great cattle call of commoditized medicine created by big data, who do you think you are? A liability risk? Please, stay normative, align your symptoms with big data. And be happy about it, dear patient, because the ends justifies the means.
Ironically, the folly of man has always been that we think we can have all the answers. Perhaps we should stop for a moment and really think about what we’re creating, courtesy of big data.
Wes Fisher is a cardiologist who blogs at Dr. Wes.