Towards quality indicators in palliative care education: An umbrella review

Palliative Care and Social Practice · Published 2026-05-01 · DOI 10.1177/26323524261440959

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Abstract

Background: The global need for palliative care is increasing. To respond effectively, all healthcare professionals who care for persons with serious illnesses should be trained to provide core palliative care. Despite increasing recognition of its importance, education remains inconsistently implemented. Objectives: To explore and identify the essential elements that define and support palliative care education, and to propose a preliminary typology of structural, process, and outcome quality indicators. Design: An umbrella review was conducted according to the Joanna Briggs Institute methodology. Data sources and methods: We systematically searched three electronic databases (CINAHL, MEDLINE, PsycInfo) for literature reviews on palliative care education. Data were analysed using a combined deductive–inductive qualitative approach. Results: Twenty-four reviews were included in the analysis. Seven structural indicators were identified relating to the training and duration of palliative care exposure, instructional format/delivery, contents, structured course development, involvement of local staff and experts, multidisciplinary and context-specific learning, and organisational support. Seven process indicators were identified, encompassing experiential learning, multi-modal approaches, reflective practice and emotional processing, group-based peer learning, embedded learning, flexibility, and feedback. Six outcome indicators were identified, including the enhancement of competencies, sustainability and long-term impact, validated tools for evaluation, participant satisfaction, integration into routine practices, and impact on patients and families. Conclusion: This umbrella review proposes an evidence-informed framework of potential quality indicators for palliative care education, offering guidance for curriculum design and policy development while identifying key areas requiring empirical refinement and validation.

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Publication details

Year
2026

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