Developing consensus on the content of a comprehensive cancer nursing model of care (the McGrath Model of Care): A modified Delphi technique protocol
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BACKGROUND: There has been significant government and non-government organisation investment in specialist cancer nursing roles in Australia with a focus on improving access to care, support and navigation. To ensure equitable access to specialist cancer nursing care, a comprehensive nursing model of care to provide supportive care to people with any type of cancer is needed AIM : The primary aim of this study is to obtain expert consensus on key components to be included in the McGrath Model of Care (MMoC). Secondary aims are to understand the feasibility of the MMoC within the Australian health care context. METHODS : A three-phase study will be conducted including: 1. development of the draft components of the MMoC through co-design and evidence synthesis; 2. expert consensus on appropriate components of the MMoC through a modified Delphi; and 3. workshops with end-users to determine feasibility of the developed MMoC. Phase 1: Themes derived from consultations with over 450+ people with lived experience of cancer; clinicians; and other key stakeholders will be synthesised with literature review results and Optimal Care Pathways to develop the draft components of the model. Phase 2: We aim to recruit 25-50 participants through direct email invitation. Participants will be experts in cancer nursing. Purposive sampling will be employed to ensure maximum variation in location of participants and representation across cancer types. Multiple rounds of an on online survey will be conducted to gain consensus on the appropriateness and necessity of components of the MMoC. Phase 3 : Qualitative workshops will be held to discuss the feasibility of relevant items in clinical practice. RESULTS : The study will be conducted between June – September 2025. CONCLUSION: The study findings will determine the final elements included in the MMoC and ensure the model is appropriate and feasible for implementation.
