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Bad CDC Data May Have Skewed Research

On Behalf of | Nov 1, 2012 | Fungal Meningitis

A commonly used database run by the Centers for Disease Control and Prevention is  fraught with serious errors, some of which indicate that patients were  impossibly pronounced dead in the emergency department, but then intubated and admitted  to the intensive care unit the same day, according to a Loma Linda University  report.

In fact, the study, which looked at 10 years’ worth of CDC data, found that one  in four emergency room patients who were reported as being intubated–which in virtually  all cases would be followed by death, admission to a critical care unit,  transfer to another facility, or transfer to surgery or a catheterization lab–was  instead reportedly discharged or referred to a non-critical care bed.

“A patient who is having a piece of plastic inserted down their windpipe is  very, very sick,” says Steven Green, MD, Loma Linda University School of  Medicine professor in California and the author of an Annals of Emergency Medicinestudy documenting the inconsistencies. “These  aren’t the kind of patients, except in very rare situations, who would be  discharged from the hospital.”

Green categorically dismisses, with a chuckle in light of Halloween festivities  this week, any suggestion the CDC anomaly could reflect the existence of  zombies, or that it is possible for a patient to be alive and dead at the same  time.

“I can’t begin to speculate on what led to these errors, but one of the  possibilities is the use of personnel who don’t have a strong command of  medical terminology,” Green says.
The CDC database in question is the National Hospital Ambulatory Medical Care  Survey or NHAMCS, which contains information on more than 350,000 emergency  department visits between 2000 to 2009, the period used by Green for his  analysis.

Among his study’s other findings, Green says, of 875 intubated patients, 27%  had incompatible dispositions. For example, 9% were reportedly discharged, 17%  were admitted to a non-critical care unit.

Green explains that the problems he’s discovered raise questions about the  veracity of research projects that used NHAMCS to draw conclusions that large  numbers of physicians don’t deliver appropriate emergency care.

“For example, you might look at study that used the NHAMCS to see what  percentage of patients with a broken bone got narcotics to treat their pain.  They found numbers that look lower than what any of us would [expect, prompting]  people to say ‘Whoa, that’s lower than it should be,’ and conclude that the  doctors are doing a bad job of treating patients’ pain.”
Likewise, another study using NHAMCS data showed that physicians weren’t always  checking for pregnancy when teenage girls came to the emergency department  complaining of abdominal pain.

“You’d see a low number and think there must be a lot of bad doctors, yet the  alternative explanation that’s suggested by the study that I’ve done is to say,  wait a minute.  Maybe there’s a problem with the underlying data.”

Green says he suspects that the personnel, who are hired by the CDC and  assigned to go to hospitals and perform chart reviews to complete the survey  and check all the boxes, may not “be trained to understand” the meaning of the  term endotracheal intubation. “If you don’t know what that means, the odds are  you’re not going to code it accurately, and that’s my worry here.”

Asked  for a response, a CDC public information representative says the agency does  not comment on journal articles that CDC personnel do not author.  Green says that after he informed a CDC  official about his results, he was told that the inconsistencies he discovered  are “under investigation.”
Going forward, he says, researchers who want to use the NHAMCS data, or  research projects stemming from it, “should have a little bit more concern  about whether the underlying data is correct.   I just worry about the hundreds of papers already out there, or in  press, and wonder how many of them have a result that is incorrect due to the  underlying data.”

Source: Health Leaders Media at

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