Keywords
Palliative Care
Nursing Informatics
Clinical Decision Support Systems
Biomedical Technology
Health Information Systems
How to Cite
Abstract
Objective: To describe the development, architecture, and construction of the knowledge base of a computational rule-based system for decision support in the Nursing Process in Oncology Palliative Care. Method: A technological innovation report guided by the SQUIRE 2.0 framework, concerning the iterative and participatory development of the PaliPEV platform in a low-code environment (AppSheet®/Google Sheets®). The knowledge base was developed by the Nursing Process Committee across 11 technical-scientific meetings, grounded in Horta's and Kolcaba's theories and a master's thesis. Thirty-one NANDA-I diagnoses were defined and aligned with NOC outcomes, NIC interventions, and nursing prescriptions, alongside the use of the Braden, Morse, and Karnofsky scales and the Edmonton Symptom Assessment System. The study was approved by a Research Ethics Committee. Results: Following an audit, 36,448 valid Nursing Processes distributed across 3,193 medical records (registrations) were identified, featuring 71,969 automatic associations and NANDA-I taxonomy completeness exceeding 99.7% across the three evaluated scenarios. The strategy was complemented by the PaliEducativa platform (35,876 accesses; 2,280 certificates issued), enabling the institution to achieve Gold Certification in a Nursing Process quality program. Conclusion: Grounded in theoretical foundations and empirical data, the iterative development proved feasible for decision support in the Nursing Process in Oncology Palliative Care, demonstrating potential for machine learning application.
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