Communicating diagnostic uncertainty

diagnostic uncertainty

My transition from medical student to practicing diagnostician was marked by one key realization: doctors don’t make definitive diagnoses. Many think that we do. Our patients are certainly under that illusion. But even at the best of times, the physician’s job to to determine the probability of disease.

We all inherently understand this. It is embedded in our discharge instructions: “if anything changes, come back to the emergency department.” But why would anything change, if we already know THE diagnosis? If this questions seems silly, it is because we have all internalized the uncertainty of medicine. We know that what is clearly a viral illness now could easily turn out to be early sepsis or pneumonia.

Unfortunately, the inherent uncertainty of medical diagnosis is easily obscured by disease labels. Tell a patient that he has gastroenteritis, and the diagnosis is made. Tell a doctor the same thing, and she will still re-examine the belly the next day to rule out appendicitis.

This is why emergency physicians are taught to make diagnoses like “chest pain not yet diagnosed” instead of “costochondritis”. The pain might seem inflammatory, but costochondritis just sounds too certain. We want to use terminology that conveys the inherent uncertainty of our diagnosis to the patient.

However, vague terminology like “shortness of breath NYD” is also problematic. Most of the time, I have a (highly) educated guess about the diagnosis. It would be a disservice to both the patient and the rest of the health care team for me to ignore my diagnostic training. The label “SOB NYD” helps no one. The label “congestive heart failure”, even if uncertain, helps guide the patient’s care.

We seem to be stuck between two extremes. “Shortness of breath NYD” is too vague; “congestive heart failure” too specific. Both labels mask the nuance and probability of diagnostics. I think we need a better option.

Why is this important? Imagine the last few patients you admitted to hospital with a diagnosis of “congestive heart failure”. Sometimes, the diagnosis is almost certain. They have a history of CHF, orthopnea, PND, no other respiratory conditions, B lines on ultrasound and xray, crackles, and an elevated JVP. Other patients are less clear. They might have a history of both COPD and CHF, with a combination of wheeze and crackle on exam, and non-diagnostic imaging. After a few hours, you decide that CHF is the most likely diagnosis, but you are far from certain.

Both of these patients will have the same admission diagnosis written on the chart. Both of those patients will leave the department with the same label. The nursing team will be told a patient is being admitted with CHF. The RT called at 3am will be told that both patients have CHF. The covering physician, as well as the team that assumes care the next day, will both see the diagnosis of CHF. But these two patients are not the same.

In writing this single diagnosis on the chart, all of your diagnostic expertise has been lost. For one patient, you were almost certain of the diagnosis, and you could have told the RT called at 3am as the patient deteriorates that CPAP or furosemide was the necessary treatment. However, for the other patient, the diagnosis was uncertain, and if they are deteriorating in the middle of the night, the most appropriate intervention might be a repeat physical exam and further testing. Unfortunately, that information is lost behind a single diagnostic label.

There must be a better way.

What if we used modifiers to indicate our level of certainty about a diagnosis? So that a patient who I am 99% sure is short of breath due to CHF receives the diagnosis of “CHF 99%” whereas a patient who I think might have CHF, but for whom multiple other diagnoses are still possible, might get the diagnosis “CHF 55%”.

A probabilistic notation would immediately help inpatient teams. It would allow them to use our diagnostic acumen, rather than trying to read our minds or restarting the diagnostic process. It would guide care overnight, when the physician is harder to reach. Perhaps, it would even empower members of the interdisciplinary team (who spend much more time with the patients than physicians do) to voice their observations, because it is now clear to them the diagnosis is uncertain.

Likewise, a probabilistic notation would probably help our outpatient teams. I can imagine my orthopedic surgeons triaging patients based on whether I thought the patient had an “ACL tear 90%” versus a “knee effusion, ACL tear 10%”. The time frame for follow up with rheumatology might be different for “temporal arteritis 99%” versus “temporal arteritis 5%”.

I know I would love to see probabilistic notations on patients I am assessing in the emergency department. Imagine you are seeing a patient who is followed by neurology for her headaches. You are seeing her at 3am and don’t have access to her old notes, but her neurologist has told her that she has migraines. Wouldn’t it be nice to know if this was a definitive diagnosis (“migraine 100”) or a provisional diagnosis (“migraine 60”)? Similarly, I see a lot of patients for repeat antibiotics for “cellulitis”. Wouldn’t it be great to know if your colleague was certain that this was infective (“cellulitis 99”) as opposed to just being cautious in a patient with chronic venous stasis (“cellulitis 10 venous stasis 90”)?

This exercise could also make us better clinicians. To start, these probabilities would likely be notations of our subjective gestalt. However, the act of writing down a probability might cause us to question how we arrived at the number. So rather than just writing “Salter-Harris 1 fracture 25%” for a child with tenderness but normal x-rays, I might decide to look into the actual base rate of the disease. The discovery that the true rate of Salter-Harris 1 fractures based on MRI is only 3% might change my practice.1 [The possibility that none of these Salter 1 injuries are clinically important is another issue altogether.]

There is generally pressure on emergency physicians to make a diagnosis. It is very difficult to admit a patient without having a provisional diagnosis. Similarly, discharged patients want to know what you think is going on. In theory, that provisional diagnosis is fine. In theory, we understand that it is provisional and probabilistic. But in practice, provisional diagnoses quickly become permanent diagnoses.

As emergency physicians, we are frequently blamed for misdiagnoses. These get labelled as errors, but calling a change in a provisional diagnosis an error is wrong. It misrepresents what emergency medicine is about. We work with limited information. Our job is to come up with a best guess, and for the most part, we do an excellent job of it. We take limited information and transform it into a provisional diagnosis that allows us to start empiric therapy. Unfortunately, the act of transcription into the chart has a way of transforming a provisional diagnosis into the final diagnosis.

Medicine is a science of uncertainty and an art of probability”

Sir William Osler2

These are just some initials thoughts. I would not want this taken too far. The act of putting a number on our diagnoses might backfire and make them seem more certain than they really are. Nor should we start quibbling among ourselves whether a diagnosis actually has a 90% or an 88% of being true.

My current solution in inelegant. I am hoping someone out there can suggest a better way. Whatever the solution, we need to embrace the role of probability in all medical diagnoses.


  1. Boutis K, Plint A, Stimec J. Radiograph-Negative Lateral Ankle Injuries in Children: Occult Growth Plate Fracture or Sprain? JAMA pediatrics. 170(1):e154114. 2016. PMID: 26747077
  2. Bean RB, Bean WB. Sir William Osler: Aphorisms from his Bedside Teachings and Writings. New York: H. Schuman; 1950
Cite this article as:
Morgenstern, J. Communicating diagnostic uncertainty, First10EM, October 31, 2016. Available at:

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