ArticleBMC medical education2026
Developing a consensus-based competency framework for hospital pharmacists in the management of advanced therapy medicinal products (ATMPs): a modified delphi study in Macao.
Article in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundAs advanced therapy medicinal products (ATMPs) increasingly enter clinical practice worldwide, many emerging markets still lack standardized pharmacy practice guidance. Macao represents one such setting where ATMP adoption is growing, yet structured competency expectations for hospital pharmacists remain limited. This study aims to develop and content-validate a competency framework (CF) for hospital pharmacists in the clinical use and management of ATMPs.
methodsA modified Delphi process incorporating the RAND/UCLA Appropriateness Method was conducted in accordance with the ACcurate COnsensus Reporting Document (ACCORD) guideline. A pharmacist expert panel (n = 15) assessed the preliminary CF through two iterative Delphi rounds using a nine-point Likert scale. Items with the disagreement index (DI) < 1 were considered appropriate for inclusion. Reliability was evaluated with Cronbach’s α and the authority coefficient (Cr).
resultsFrom the 53 potential competencies derived from a previous literature review, international guidelines, and expert opinions, all items were rated as appropriate by 15 panelists in the first Delphi round. However, revisions were proposed for 33 items based on appropriateness ratings and qualitative feedback. The revised CF was re-evaluated by 14 panelists in the second Delphi round, during which nine items were further refined to finalize the CF. Panelist feedback primarily focused on defining pharmacists’ responsibilities in ATMP management, ensuring quality assurance, clarifying procedures for preparation, dispensing, and transportation, and specifying the roles of pharmacy technicians in Macao hospitals. The finalized CF delineates pharmacists’ core competencies across six domains, covering ATMP governance and compliance, prescription evaluation, handling and storage, preparation processes, issue and transportation, administration and monitoring. Cronbach’s α indicated high internal consistency (0.975–0.979), and the average expert authority coefficients were satisfactory (0.70) in both rounds.
conclusionA consensus-based CF specific for pharmacists involved in ATMP management was developed in Macao, and its content validity was supported through a modified Delphi process. This CF provides a structured basis for strengthening pharmacists’ competencies and offers a transferable reference for policy and practice across other emerging healthcare systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.