JOURNAL ARTICLE

Insomnia in ambulatory care: A clinical review.

  • Published In: American Journal of Health-System Pharmacy, 2025, v. 82, n. 6. P. 265 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Dopheide, Julie A; Roth, Winter R; Chu, Michelle K L 3 of 3

Abstract

This clinical review focuses on the causes, assessment, and evidence-based treatment options for insomnia in ambulatory care outpatients. It emphasizes the importance of screening for coexisting conditions such as obstructive sleep apnea, restless legs syndrome, narcolepsy, psychiatric disorders, and substance use disorders, as well as documenting the type and duration of insomnia. Cognitive behavioral therapy for insomnia (CBT-I), including digital delivery, is recommended as the first-line treatment, with pharmacological options such as prescription hypnotics (benzodiazepine receptor–active agents, Z-hypnotics, dual orexin receptor antagonists) and off-label medications (e.g., trazodone, mirtazapine) reserved for short-term or specific cases. Nonprescription treatments like antihistamines and melatonin have limited efficacy and are recommended only for select populations. Treatment decisions should consider patient age, comorbidities, and insomnia type, with pharmacotherapy used at the lowest effective dose and shortest duration to minimize risks such as next-day impairment, dependence, and adverse effects.

Additional Information

  • Source:American Journal of Health-System Pharmacy. 2025/03, Vol. 82, Issue 6, p265
  • Document Type:Article
  • Subject Area:Complementary and Alternative Medicine
  • Publication Date:2025
  • ISSN:1079-2082
  • DOI:10.1093/ajhp/zxae255
  • Accession Number:183547723
  • Copyright Statement:Copyright of American Journal of Health-System Pharmacy is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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