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[Factors associated with involuntary hospital admissions in technology-dependent children]
Aline Cristiane Cavicchioli Okido1, Juliana Coelho Pina2, Regina Aparecida Garcia Lima3
1Escola de Enfermagem de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil.
Insights
Involuntary hospital admissions for technology-dependent children are linked to medication quantity, which increases risk. Conversely, older age and more devices act as protective factors against such admissions.
Area of Science:
- Pediatric healthcare
- Public health
- Medical technology
Context:
- Technology-dependent children require specialized care.
- Involuntary hospital admissions present a significant challenge in pediatric healthcare.
- Understanding admission factors is crucial for improving care for vulnerable children.
Purpose:
- To identify factors associated with involuntary hospital admissions in technology-dependent children.
- To develop an explanatory model for hospital admissions in this population.
Summary:
- A cross-sectional study analyzed 102 technology-dependent children (6 months-12 years).
- Higher medication quantity was a risk factor (OR=1.532), while older age (OR=0.991) and more devices (OR=0.387) were protective factors.
- Generalized Linear Models were used for data analysis.
Impact:
- Provides data to inform care strategies for technology-dependent children.
- Offers an explanatory model to understand and potentially reduce involuntary hospital admissions.
- Contributes to improving healthcare outcomes for children requiring medical technology.
Objective:
To identify the factors associated with involuntary hospital admissions of technology-dependent children, in the municipality of Ribeirão Preto, São Paulo State, Brazil.
Method:
A cross-sectional study, with a quantitative approach. After an active search, 124 children who qualified under the inclusion criteria, that is to say, children from birth to age 12, were identified. Data was collected in home visits to mothers or the people responsible for the children, through the application of a questionnaire. Analysis of the data followed the assumptions of the Generalized Linear Models technique.
Results:
102 technology-dependent children aged between 6 months and 12 years participated in the study, of whom 57% were male. The average number of involuntary hospital admissions in the previous year among the children studied was 0.71 (±1.29). In the final model the following variables were significantly associated with the outcome: age (OR=0.991; CI95%=0.985-0.997), and the number of devices (OR=0.387; CI95%=0.219-0.684), which were characterized as factors of protection and quantity of medications (OR=1.532; CI95%=1.297-1.810), representing a risk factor for involuntary hospital admissions in technology-dependent children.
Conclusion:
The results constitute input data for consideration of the process of care for technology-dependent children by supplying an explanatory model for involuntary hospital admissions for this client group.
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