Mark Cuban got into an interesting debate with Charles Ornstein (and much of the health wonk Twitter community) over whether more lab testing is better. It began when he advocated that everyone get quarterly lab testing:
While I’m a fan of Cuban’s Shark Tank, and I respect his business acumen immensely, there are a couple of things wrong with this. It’s worth discussing them in detail.
First of all, people presume that tests are binary things. They’re not. When you get a blood test, it doesn’t come back “sick” or “well”. It comes back with a number value. Let’s say you’re looking at WBC, or the number of white blood cells. You might get a reading of 7.0, which refers to the number of thousands in a milliliter. Is that good? Maybe. We think that most people should have a value of 4.5 – 10, but only because that’s the range where most people fall. Further, there’s no real meaning to the relative value. 6 isn’t better than 9, or vice versa.
Let’s say you get a 11. Are you sick? I don’t know. White blood cell levels can be affected by so many things, like infections, allergies, or even stress. Do you have symptoms? Do you have other issues? If someone got this value without any other data – I’d have no idea what to do with it. You have to interpret it – in context – and that can’t be done by a lay person quarterly. Moreover, these numbers can change all the time, with no correlation to anything we can recognize. It’s not like if you’ve been 6 for years, and were suddenly 8, that you should worry.
This is why I teach residents and medical students never, ever to order blood tests unless they are looking for a specific problem. Do you think that the patient is anemic? Then it makes sense to check a hematocrit value (the number of red blood cells). Are you worried they might have diabetes? Then you should check a glucose value. But getting those tests in a vacuum isn’t helpful at all.
This leads to the second problem. When a lab test picks up something that isn’t real, it’s called a false positive. It’s a lab value that is “abnormal” but there really isn’t a health issue. When someone is healthy, an abnormal value is much more likely to be a false positive than a true positive. This is especially true when a test has a low “specificity“.
Specificity is a test characteristic which refers to the proportion of people who are healthy who have a negative test. If it’s low, then it means that too many healthy people are having a positive test. A random blood test would have a very low specificity, because an abnormal value would have a disproportionately high probability of being wrong in predicting whether you should be concerned.
This leads to a third problem. How do you react to an abnormal value? As a colleague once said to me, “Ordering a lab test is like picking your nose in public. If you find something, you better know what you’re going to do with it.”
Most people, even physicians, have a hard time ignoring “abnormal” lab values. They want to work them up. This leads to excess testing, potential harm, and a lot of money wasted. False positives are just that – false. You wind up on a “diagnostic Odyssey” where you chase abnormal value after abnormal value, and never get to the end.
I’ll give you an anecdote to illustrate this. When I was in medical school, I had some belly pain that was pretty bad. I was admitted to the hospital, which was overkill, and it resolved overnight; I was absolutely fine the next day. But since I was a med student, they didn’t want to miss anything. They got extra tests, even though I was healthy. There were some abnormal values, and they felt compelled to follow them up. I eventually wound up having every test you can imagine including CT scans, echocardiograms, x-rays, endoscopy, and even cystoscopy (go look that up to sympathize with me). In each test, something else “abnormal” was found. None of them led to any real problems or diagnoses. They were all pretty much false positives, because I was healthy.
I understand what Cuban is driving at. We’ve all been told that data are important and that more is the future. But it’s important to understand the difference between using data in the aggregate to generate hypotheses, and using data on individuals to make decisions. Collecting blood from millions of people many times during the year might help us to learn new things about detecting disease in the future. It’s great for research and even investment. But it’s not clear it’s good for any one person. We don’t know what to do with the results at this point.
We should get tests when we have evidence that they will help. We should get them when we expect they will do more good than harm. At this time, there’s no reason to believe that for any individual, quarterly blood tests would fit these criteria.
