How Doctors Diagnose Things (An Explanation of COVID-19 Testing Criteria)

correlation
Image credit: xkcd.com

I’m going to pause in my evaluation of the Medicare for All Act of 2019 just for a week to write as a physician for once rather than as a health policy researcher. And not to talk about coronavirus (SARS-CoV-2) so much as to explain a principle of clinical medicine I wish more people would understand, especially now when it’s particularly relevant.

Let me explain to you how doctors diagnose things.

Any diagnostic effort a physician does starts with making a list of possible causes of the patient’s problem. That list is called a “differential diagnosis,” or a “differential,” for short. Only when you have determined your differential can you make decisions about how to proceed working up or treating a problem.

Together, the likelihood of all those things on the differential add up to 100%. If one of those things goes up in likelihood (say, because of a positive test for that thing), by definition the other things on the differential go down in likelihood.

So, for example, the patient I saw today. She hadn’t traveled anywhere recently, she hasn’t been exposed to anyone with COVID-19, and she doesn’t live in an area where there are many COVID-19 cases–all in all, she was very low risk for having COVID-19. But some food she ate yesterday didn’t sit well, and she vomited but also tried to take a breath at the same time. That didn’t work out so well, and she was trying to cough the vomit out of her lungs after that. About a day later, she was still coughing and short of breath, but now she was having fevers. COVID-19 was on the differential (cough, shortness of breath, fever), but bacterial pneumonia secondary to aspiration was much more likely. Did we need to test this lady?

With the information I’ve given you, the answer is probably no. We are pretty certain her symptoms were from that aspiration event, which makes COVID-19 very unlikely.

But some patients with that same story would still get tested (which was the case with this patient), as I’ll explain using the principle of a “testing threshold.”

Every item on the differential diagnosis sits somewhere on the probability spectrum in between 0% and 100%. If you test for the disease, and the test comes back negative, it pushes that one down closer to 0%. (How far it pushes it toward 0% depends on how reliable the test is.) And if the likelihood of something on the differential is close enough to 0%, then you say it’s unlikely enough that you can essentially think of it as being ruled out.

How close is “close enough to 0%”? Or, in other words, how unlikely does something have to be before we don’t feel the need to test for it further? Or, in other other words, how do we decide where to set that testing threshold? That depends on a few things, especially how risky it is to miss the diagnosis. If we’re dealing with the patient above, and I told you she’s a 25 year old with no medical problems and she works from her computer at home, it’s not very risky to miss the diagnosis, and we’d counsel her to make sure she’s isolated until a few days after all her symptoms have resolved. But if that patient is 80 years old and has severe COPD, this is an incredibly high risk individual, and missing a COVID-19 diagnosis, unlikely as it is, would be catastrophic, so we would definitely test her.

Similarly, young healthy healthcare providers are considered high risk because of the potential consequences of missing that diagnosis in them. The consequences are not to them directly, but rather the consequences are to their patients they could potentially spread it to, many of whom are likely elderly or high risk in other ways. Therefore, healthcare workers’ testing threshold is also set very low.

So, if you have symptoms, check testing criteria. Call a hotline. They will ask you questions to figure out where your testing threshold is, and based on that they will decide if you need to get tested or not.

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