Abstract
AIMS AND OBJECTIVES: The study aims to derive a conceptual model of an ecosystem of a patient in their home environment, integrating principles from biological ecosystem theory to enhance holistic, home-based care for patients with non-communicable diseases. METHODOLOGICAL DESIGN AND JUSTIFICATION: A concept derivation approach was employed due to the absence of any clear definition of the patient ecosystem at home concept. ETHICAL ISSUES AND APPROVAL: As a conceptual study, ethical considerations were minimal. Ethical standards were upheld during the literature review, and ethical approval was not required. RESEARCH METHOD: Concept derivation was used to derive the concept from biology and apply it to the patient's home. The process involved four steps: a literature review, cross-disciplinary exploration, selection of the parent concept, and a redefinition of the concept in the context of patients at home. OUTCOME MEASURES: The conceptual clarity, structure, and applicability of the derived model of the patient ecosystem served as measures of the outcomes. These include the identification and integration of the ecosystem's key components, such as the environment, living elements, processes, and structure, and their relevance for supporting patients at home. RESULTS: The main outcome is a conceptual model of the patient ecosystem at home that highlights dynamic interactions within the ecosystem and stresses patient agency and collaboration between informal, formal, and virtual support networks. As ecosystem managers, nurses play a crucial role in supporting the patient ecosystem's capability to provide homeostasis. STUDY LIMITATIONS: As a conceptual model not yet empirically validated, its applicability may vary across cultural and socioeconomic contexts. CONCLUSIONS: The proposed patient ecosystem model provides a novel framework for understanding and supporting patients at home, facilitating efficient resource utilisation and adding to the quality of life for patients and family members. While offering theoretical insight, further validation and cross-sector collaboration are essential before implementing the model in practice.