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Many Physicians Choose Insomnia Meds Based on Habit Rather Than Patient’s Symptoms, Medical History

Many Physicians Choose Insomnia Meds Based on Habit Rather Than Patient’s Symptoms, Medical History
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Harvard Medical School


Harvard Medical School (click to view)

Harvard Medical School

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Clinical decision-making and treatment choice is a complex cognitive process influenced by multiple variables, report researchers.

Clinical decision-making is a complex process, driven by multiple factors, including social and psychological dynamics, peer pressure and even exposure to drug advertising.

Now research from Harvard Medical School shows that when it comes to a physician’s choice of insomnia medication, habit may trump all else.

The results suggest that many clinicians choose insomnia drugs somewhat reflexively, based on routine, rather than by taking into account a patient’s symptoms and medical history. Indeed, the analysis showed that a physician’s past prescribing pattern, rather than patient characteristics, was the more potent predictor of what insomnia medication a patient might get.

Findings of the research, based on analysis of 1,105 patients’ medical records and the accompanying clinical notes, appear Feb. 9 in Scientific Reports.


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“Our results illuminate the notion that just as everyone else, many physicians are creatures of habit who tend to rely on cognitive shortcuts in their decision-making,” said study first author Andrew Beam, a postdoctoral research fellow in the Department of Biomedical Informatics at HMS. “Doctors are not always as rational as we’d like to believe.”

In their analysis, the researchers focused on the two most commonly prescribed drugs: zolpidem, a newer medication with a great efficacy record but associated with side effects such as next-day drowsiness and dizziness, and trazodone, an older drug typically used for depression that is less effective for insomnia but has a well-established safety profile. How and why physicians choose one drug over another remains unclear so the HMS team set out to untangle the factors that drive clinical choice.

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