JOURNAL ARTICLE

Implementation of pharmacist-led services for sexual and gender minorities: A multisite descriptive report.

  • Published In: American Journal of Health-System Pharmacy, 2024, v. 81, n. 8. P. 316 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Phan, Tam; Astle, Kevin N; Mills, Alex R; Medlin, Christopher G; HERMAN, DAVID 3 of 3

Abstract

This article examines the implementation of pharmacist-led clinical services tailored to sexual and gender minority (SGM) populations across three U.S. states—California, Mississippi, and Florida—highlighting variations in services, legislative environments, and pharmacist scope of practice. Services provided by clinical pharmacists include management of gender-affirming hormone therapy (GAHT), HIV antiretroviral (ARV) medication adherence and preexposure/postexposure prophylaxis (PrEP/PEP) counseling, chronic disease management, mental health support, and sexual health care. The study underscores the impact of differing state laws and regulatory barriers on service delivery and advocates for culturally humble, collaborative approaches involving pharmacists, healthcare systems, academic institutions, and community organizations to improve health outcomes and reduce disparities in SGM populations. It also emphasizes the importance of legislative harmonization and expanded pharmacist scope of practice to enhance access to affirming, patient-centered care.

Additional Information

  • Source:American Journal of Health-System Pharmacy. 2024/04, Vol. 81, Issue 8, p316
  • Document Type:Article
  • Subject Area:Consumer Health
  • Publication Date:2024
  • ISSN:1079-2082
  • DOI:10.1093/ajhp/zxad328
  • Accession Number:176466077
  • 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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