What About Diagnostic Errors?

Much of the discussion about applying a lean approach to healthcare focuses on reducing or eliminating medical errors – for example, giving someone the wrong medication, performing the wrong procedure, or not delivering the appropriate treatment.

But in his blog Wachter’s World, Dr. Robert Wachter, Professor and Associate Chairman of the Department of Medicine at the University of California, San Francisco, raises an interesting question: Can anything can also be done about diagnostic errors?

It is an important question. Wachter notes that diagnostic errors comprised 17 percent of the adverse events in a Harvard Medical Practice Study and account for twice as many malpractice suits as medication errors.

He comments,

As the quality and safety movements gallop along, the need to fix Diagnostic Errors Exceptionalism grows more pressing. Until we do, we will face a fundamental problem: a hospital can be seen as a high quality organization – receiving awards for being a stellar performer and oodles of cash from P4P programs – if all of its “pneumonia” patients receive the correct antibiotics, all its “CHF” patients are prescribed ACE inhibitors, and all its “MI” patients get aspirin and beta blockers.

Even if every one of the diagnoses was wrong.

What can be done? Wachter says there are two broad categories of solutions. One is training doctors in “better thinking,” which can be difficult. The other is supplementing the doctor’s efforts with analysis from Artificial Intelligence, which has been tried in the past without great success (though technology keeps improving).

Neither approach attracts a lot of attention or funding. Wachter makes a good point in suggesting that the most important first step is generating more interest in the issue. He recently spoke about it at a conference on diagnostic errors sponsored by the Agency for Healthcare Research and Quality. He suggests that the simple fact the conference was held is a good sign.

It makes tremendous sense to apply lean strategies to reducing medical errors. But can they also be applied to reducing diagnostic errors?

What do you think?