Doctors are Bad at Reading Lab Results
Written by Editor   
Tuesday, April 16, 2019 07:43 PM

Modern medicine has come to rely on tests and technological scans. Every year, doctors in this country order more than 4 billion tests. 

Research has found, however, that many physicians misunderstand test results or think tests are more accurate than they are when used diagnostically. Doctors especially fail to grasp how false positives work, and they make crucial medical decisions based on incorrect assumptions that patients have ailments that they probably don’t, unacceptably increasing the chances of making the wrong choice. 

The first problem that doctors (and thus, patients) face is a basic misunderstanding of probability. Say that Disease X has a prevalence of 1 in 1,000 (meaning that 1 out of every 1,000 people will have it), and the test to detect it has a false-positive rate of 5 percent (meaning 5 of every 100 subjects test positive for the ailment even though they don’t really have it). If a patient’s test result comes back positive, what are the chances that she actually has the disease?  

Researchers in a study found that almost half of doctors surveyed said patients who tested positive had a 95 percent chance of having Disease X.  This is radically, catastrophically wrong. In fact, it’s not even close to right. 

Imagine 1,000 people, all with the same chance of having Disease X. We already know that just one of them has the disease. But a 5 percent false-positive rate means that 50 of the remaining 999 would test positive for it nonetheless. That means 51 people would have positive results, but only one of those would really have the illness. So if your test comes back positive, your true chance of having the disease is actually 1 out of 51, or 2 percent — a heck of a lot lower than 95 percent.

A 5 percent false-positive rate is typical of many common tests. The primary blood test to check for a heart attack, has a 5 percent false-positive rate. U.S. emergency rooms often administer the test to people with a very low probability of a heart attack; as a result, 84 percent of positive results are false. These false-positive tests often lead to  expensive and sometimes invasive testing.

In one study, gynecologists estimated that a woman whose mammogram was positive had a higher than 80 percent chance of having breast cancer; the reality is that her chance is less than 10 percent. Of course, women who have a positive mammogram often undergo other tests, such as an MRI and a biopsy, which can offer more precision about the presence of cancer. But researchers have found that even after the battery of exams, about 5 of every 1,000 women will have a false-positive result and will be told they have breast cancer when they do not.  The confusion has serious consequences. unnecessary treatment, surgery, radiation or chemotherapy.

Studies have found that doctors make similar errors with other tests, including those for prostate and lung cancer, heart attack, asthma and Lyme disease. Of course, no test is perfect, and even very careful, statistically sophisticated doctors can sometimes make mistakes. That’s not the problem. Too many do not understand that many of the tests they rely on are deeply fallible. 

In another study results showed 90 percent of the patients received at least one unnecessary test and that, overall, nearly one-third of all the tests were superfluous. When patients receive tests that aren’t needed, there is a reasonable chance that doctors are using the results to make choices about treatment; by definition, these choices have a higher danger of being flawed.

Doctors also tend to overuse some tests. To be fair, it is not surprising that doctors tend to overestimate the precision and accuracy of medical tests. The companies that provide tests work hard to promote their products. Doctors often think that ordering more tests will protect against lawsuits. Moreover, medical schools offer limited instruction on how to understand test results, which means many doctors are not equipped to do this well. Even when medical students have short classroom instruction in test interpretation, it is rarely taught in a clinic with actual patients.

One key step is for doctors to acknowledge the gaps in our understanding and to improve our knowledge of what each test can accurately tell us. Medical schools and professional associations can also do a much better job of educating doctors to understand how risk and probability work. Patients must also play an important role. They should realize that doctors, even quite capable ones, may not fully understand the statistical underpinning of the tests they use. 

Basic misunderstandings about how tests work and how accurate they are contribute to a bigger problem. Although precise numbers are hard to come by, every year, many thousands of patients are diagnosed with diseases that they don’t have. They receive treatments they don’t need, treatments that may have harmful side effects. Perhaps just as important, they and those around them often experience enormous stress from these incorrect diagnoses. Treating nonexistent diseases is wasteful and often expensive, not only for patients but for hospitals, insurance companies and governments.  It is a public safety issue.