There are times when the diagnosis announces itself as the patient walks in, because the body is, among other things, a text. I’m thinking of the icy hand, coarse dry skin, hoarse voice, puffy face, sluggish demeanor and hourglass swelling in the neck — signs of a thyroid that’s running out of gas. This afternoon the person before me in my office isn’t a patient but a young physician; still, the clinical gaze doesn’t turn off, and I diagnose existential despair."For every one hour we spend cumulatively with patients, studies have shown, we spend nearly two hours on our primitive Electronic Health Records..."
Let’s not call this intuition — an unfashionable term in our algorithmic world, although there is more to intuition than you think (or less than you think), because it is a subconscious application of a heuristic that can be surprisingly accurate. This physician, whose gender I withhold in the interest of anonymity and because the disease is gender-neutral, is burned out in what should be the honeymoon of a career. Over the years, I have come to recognize discrete passages in a medical life, not unlike in Shakespeare’s “Seven Ages of Man” — we have our med-school equivalent of “the whining schoolboy with his satchel and shining morning face” and the associate professor “jealous in honor, sudden and quick in quarrel.” But what I see in my colleague is disillusionment, and it has come too early, and I am seeing too much of it.
Does this physician recall sitting before me as an idealistic first-year medical student, keen to take the world in for repairs? It was during those preclinical years that the class learned to use the stethoscope, the ophthalmoscope and the tendon hammer, to percuss the body, sounding out its hollows, the territorial boundaries of lung and liver. After the preclinical come the two clinical years, though I think of those phases these days as precynical and cynical. When students arrive on the wards full time, white coats packed with the aforementioned instruments, measuring tape, tuning fork, flashlight and Snellen eye chart, they are shocked to find that the focus on the ward doesn’t revolve around the patients but around the computers lining the bunkers where students, residents and attending physicians spend the majority of their time, backs to one another. All dialogue among them and other hospital staff members — every order, every lab request and result — must pass through this electronic portal, even if the person whose inbox you are about to overload is seated next to you.
In America today, the patient in the hospital bed is just the icon, a place holder for the real patient who is not in the bed but in the computer. That virtual entity gets all our attention. Old-fashioned “bedside” rounds conducted by the attending physician too often take place nowhere near the bed but have become “card flip” rounds (a holdover from the days when we jotted down patient details on an index card) conducted in the bunker, seated, discussing the patient’s fever, the low sodium, the abnormal liver-function tests, the low ejection fraction, the one of three blood cultures with coagulase negative staph that is most likely a contaminant, the CT scan reporting an adrenal “incidentaloma” that now begets an endocrinology consult and measurements of serum cortisol.
The living, breathing source of the data and images we juggle, meanwhile, is in the bed and left wondering: Where is everyone? What are they doing? Hello! It’s my body, you know!…
My young colleague slumping in the chair in my office survived the student years, then three years of internship and residency and is now a full-time practitioner and teacher. The despair I hear comes from being the highest-paid clerical worker in the hospital: For every one hour we spend cumulatively with patients, studies have shown, we spend nearly two hours on our primitive Electronic Health Records, or “E.H.R.s,” and another hour or two during sacred personal time. But we are to blame. We let this happen to our trainees, to ourselves.
How we salivated at the idea of searchable records, of being able to graph fever trends, or white blood counts, or share records at a keystroke with another institution — “interoperability”! — and trash the fax machine. If every hospital were connected, we would have a monster database, Big Data that’s truly big and that would allow us to spot trends in disease so much earlier and determine best practice and predict complications. But we didn’t quite get that when, as part of the American Recovery and Reinvestment Act of 2009, $35 billion was eventually steered toward making medicine paperless.
My A.T.M. card is amazing: I can get cash and account details all over America and beyond. Yet I can’t reliably get a patient record from across town, let alone from a hospital in the same state, even if both places use the same brand of E.H.R., for reasons that are only partly explained by software that has been customized for each site. This is not like sending around a standard Word file. And so, too often the record comes by fax.
What the E.H.R. has done is help reduce medication errors; it is a wonderful gathering place for laboratory and imaging information; the notes are always legible. But the leading E.H.R.s were never built with any understanding of the rituals of care or the user experience of physicians or nurses. A clinician will make roughly 4,000 keyboard clicks during a busy 10-hour emergency-room shift. In the process, our daily progress notes have become bloated cut-and-paste monsters that are inaccurate and hard to wade through. A half-page, handwritten progress note of the paper era might in a few lines tell you what a physician really thought. (A neurosurgeon I once worked with in Tennessee would fill half the page with the words “DOING WELL” in turquoise ink, followed by his signature. If he deviated from that, I knew he was very worried and knew to call him.) But now, with a few keystrokes, you can populate your note with all the listed diagnoses, all the medications, all the labs, all the radiology reports, pages and pages of these, as well as enough “smart phrases” — “.EXT2” might spit out “Extremities-2+ pedal edema, normal pulses” — to allow you to swear you personally examined the patient from head to foot and personally took all the elements of the history, personally did a physical exam separate from the admitting physician that would put Sir William Osler to shame, all of which make it possible to bill at the highest level for that encounter (“upcoding”)...
I'm still having trouble believing that. It is, however, an empirical matter, vague "studies have shown" anecdotes aside. (See, e.g., my 2014 riff on data-mining the EHR security logs for workflow analytics.)
Read the entire NY Times piece.
apropos, see a couple of my prior posts: "Are structured data the enemy of health care quality?" and "Clinical cognition in the digital age."
And, of course, we musn't forget English major @Healthcare_Kate's swell "EHRs are a dying technology."
The NY Times article headline cites 'Machine Learning." But, I've noted possible "reproducibility problems."
Finally (for now). see my post "Fix the EHR?" Of course, but how about fixing the clinical process workflows?
ERRATA
Five weeks since my daughter died. Still seems like last night. Sigh...
Next up for me? The SAVR px. Just thrilled. Meeting with my Primary and my Cardiologist tomorrow, then the Cardiac Surgeon next Tuesday. I had a coronary angiogram done. Negative for blockages, so I'm looking at "just" a straight aortic valve job.
BTW, Danielle's former employer has launched the Danielle L. Gladd Scholarship Fund in her honor and memory. I just contributed.
UPDATE
Another cautionary tale regarding medical charts, this one having zilch to do with keystrokes and mouse clicks.
Your Medical Chart Might be Biased. Here’s What Doctors Should Do About It.Seriously doubt that digital "AI/NLU" (Natural Language Understanding) tech portends any help there.
Racial disparities in health outcomes are complicated, but this is one place to start.
By DANIELLE OFRI
…A recent paper caught my eye because it captured one of the more subtle aspects of the brew: how we write about patients in the chart. Mary Catherine Beach and her colleagues at Johns Hopkins University were curious about whether our choice of language transmits bias from one medical professional to another. The researchers created a hypothetical case of an African American man with sickle cell disease, a condition that typically requires opiate medications for control of painful flares. They wrote two versions of the medical chart, one with neutral language and one with language—taken from real charts—that could be viewed as more stigmatizing. Medical students and residents were randomized to read one of the charts and then asked about their attitude toward the patient and how much pain medication they would prescribe.
Those trainees who read the chart with the more stigmatizing language exhibited more negative attitudes toward the patient and elected to give less aggressive pain treatment. This result is probably not surprising—we know that black patients tend to receive lower rates of pain treatment. But what is intriguing is how subtle the differences in language were between the two charts. In the first chart, the patient was described as a “28-year old man with sickle cell disease” and in the second chart as a “28-year old sickle cell patient.” Before the symptoms occurred the patient “spent yesterday afternoon with friends” versus “was hanging out with friends outside McDonalds.”
For the physical examination, the doctor observed in the first chart that the patient “is in obvious distress,” and in the second that the patient “appears to be in distress.” A nursing note in the first chart reported that the patient “is not tolerating the oxygen mask and still has 10/10 pain,” and in the second chart that the patient “refuses to wear his oxygen mask and is insisting that his pain is ‘still a 10.’ ”
The descriptions in the second chart weren’t necessarily inaccurate, but together they subtly paint the patient as a less reliable person, someone who perhaps is trying to game the system for drugs. According to Beach, this type of language not only discredits the patient’s report of pain, but highlights details that reinforce negative stereotypes. Medical charts are the primary means of communication among medical professionals, so this sort of language covertly signals to other members of the team that this is a ‘low class’ person who isn’t trustworthy or deserving.
As soon as Beach put it this way, I could see that our supposedly objective medical records contain racially laden dog whistles of the sort that we regularly decry in political speech. In the last two years we’ve gotten more adept at noticing and calling out references to inner cities, illegal aliens, international bankers, Sharia law, and locker-room talk, but we doctors like to think that we treat all our patients equally. We would never think of ourselves as racist or marginalizing. Yet, it’s there in our language…
I love Dr. Ofri's work, and have cited her many times.
Numerous relevant Danielle Ofri articles up on Slate, btw.
I'd like to know what Rachel Pearson ("@HumanitiesMD") thinks about the foregoing. I keep bugging her about wanting to read her Doctoral Dissertation, to no avail as yet. "You must be the only person in the country who wants to read it."
Summary of Dissertation:All part of a piece, 'eh?
Objectivity is an epistemological virtue that physicians aspire to embody in our practice. Historians and philosophers have pointed out that objectivity is culturally specific: it varies with time, place, and profession. In pre-clinical training, physicians learn to honor a scientific version of objectivity, in which the self is understood primarily as a potential source of error and “scientific selves” seeks to eradicate the pernicious influence of the self from scientific data. In practice, however, this research identifies that medical objectivity is distinct from scientific objectivity. This dissertation examines memoirs of medical training to understand how physician trainees learn, experience, and use objectivity...
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More to come...
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