Proceedings of the 8th World Conference on Qualitative Research

Abstract

Introduction
Optimizing nursing care throughout the life cycle continues to be a challenge for nursing care. Any change in the ventilation pattern demands the need for interventions to adequately manage signs and symptoms and improve ventilation.
After a comprehensive review with the aim of determining the effectiveness of non-pharmacological interventions in pulmonary ventilation and their impact on respiratory function, there is a need for the Portuguese population to define clinical reasoning in a nursing ontology
Aims
This study analyze all nursing interventions related to compromised ventilation in the Portuguese context, determine which essential data indicate non-intentional intervention and propose a new set of interventions that represent nursing actions related to compromised ventilation that can be integrated into the clinical data model in the computer application.
Methods
Two focus groups (FG) were held online on the Colibri platform, each with twelve Nurses specializing in Rehabilitation Nursing and Nurses specializing in Pediatrics, Nurses specializing in Medical Surgery with clinical experience in the respiratory area. The qualitative analysis of the findings was carried out by two independent researchers, according to Bardin's content analysis technique. This study was authorized by the ethics committee UCP-project nº 130/2021
Results: In the content analysis, the categories emerged: Data, Interventions, Adaptive process, Care partnership, child development, existing resources and clinical data model. Participants corroborated the need for a clinical model of data sensitive to the assessment of the individual's and caregiver's capacity, knowledge, attributed meanings, participation and involvement of the patient that contributes to mastery. A system that allows the assessment of self-efficacy in the disease process.
Conclusions
This study points to the creation of a clinical data model that relates data with diagnoses, objectives with interventions that can be integrated into personalized electronic health records. Promotes the adoption of a nursing ontology for electronic health records.