JOURNAL ARTICLE

Use of two general-purpose scales to assess clinical pharmacy activities in a cell transplantation unit.

  • Published In: Journal of Oncology Pharmacy Practice, 2026, v. 32, n. 3. P. 507 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Quinet, Florence; Gilliot, Sixtine; Beauvais, David; Vasseur, Michele; Srour, Micha; Magro, Léonardo; Coiteux, Valérie; Chauvet, Paul; Yakoub-Agha, Ibrahim; Odou, Pascal; Décaudin, Bertrand; Simon, Nicolas 3 of 3

Abstract

This article focuses on evaluating drug-related problems (DRPs) and pharmacist interventions (PIs) in a French hematopoietic cell therapy (HCT) unit using two general-purpose scales: the Act-IP scale for classifying DRPs and PIs, and the Clinical, Economic and Organisational (ClEO) scale for assessing the impacts of PIs. The study retrospectively analyzed 382 DRPs and PIs recorded between 2018 and 2021, finding that drug-drug interactions, physicochemical incompatibilities, and drug monitoring issues were the most frequent DRPs, while PIs related to drug monitoring were most common and often clinically significant. Over 60% of PIs had at least a moderate positive clinical impact, all were rated as having a positive organizational impact, and economic impacts were balanced between cost increases and savings. The findings suggest that, with slight adaptation, the Act-IP scale can effectively map clinical pharmacy activities in HCT units and that pharmacist interventions contribute positively to patient care and organizational outcomes.

Additional Information

  • Source:Journal of Oncology Pharmacy Practice. 2026/04, Vol. 32, Issue 3, p507
  • Document Type:Article
  • Subject Area:Pharmacy and Pharmacology
  • Publication Date:2026
  • ISSN:1078-1552
  • DOI:10.1177/10781552241297391
  • Accession Number:193124282
  • Copyright Statement:Copyright of Journal of Oncology Pharmacy Practice is the property of Sage Publications Inc. 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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