Mayo Clinic phasing out Ambien because of study findings.
The sleep drug Ambien (zolpidem) greatly increases hospital patients’ risk of falling, a new study finds.
Researchers from the Mayo Clinic in Rochester, Minn., looked at data on more than 16,000 hospitalized patients and found that the fall rate for those who took Ambien was more than four times higher than for those who did not take the drug — just over 3 percent compared with 0.7 percent.
Ambien is a commonly used sleep drug in hospitals, according to the study, published Nov. 19 in the Journal of Hospital Medicine.
“As a result of our study, we are now phasing out [Ambien] and moving toward sleep enhancement techniques that are not based on drugs and which we believe are safer and probably as effective,” Dr. Timothy Morgenthaler, Mayo’s chief patient safety officer, said in a journal news release.
The fall risk posed by the drug was greater than that posed by factors such as age, mental impairment, delirium or insomnia, regardless of the dosage used, according to the study authors.
“Ensuring that people get enough sleep during their hospital stay is very important, but it can also prove very challenging,” said Morgenthaler.
“Patient falls are also a significant patient safety issue in hospitals and one that has been quite difficult to tackle, despite considerable efforts. That is why it is one of the target aims of the U.S. Department of Health and Human Services Partnership for Patients project,” said Morgenthaler, who specializes in sleep disorders and pulmonary and critical care.
“Our hospitals have an overall fall rate of about 2.5 per 1,000 patient days, which is lower than many national benchmarks,” he said. However, Mayo has been unable to make a significant dent in that rate in recent years. “Now, we calculate that for every 55 patients who received [Ambien], there was one additional fall that may have been avoided by not administering the drug,” Morgenthaler said.
Although the study found an association between Ambien use and falls, it did not prove a cause-and-effect relationship.
By Robert Preidt