Intervenciones enfermeras más prevalentes en la atención de adultos ingresados en unidades de hospitalización

Autor: Margarita Medina Torres, Alberto Rando Caño, Tomás Sebastián Viana, Montserrat Solís Muñoz, Juan José Granizo Martínez, Paloma Perez-Serrano liaño, María Nieves Moro Tejedor, Natalia Mudarra García, Susana Arias Rivera
Rok vydání: 2021
Předmět:
Zdroj: Metas de Enfermería. 24
ISSN: 1138-7262
DOI: 10.35667/metasenf.2021.24.1003081766
Popis: Objective: to identify the most prevalent Nursing interventions in adult patient care in the setting of hospitalization units. Method: a study with multi-method and multicenter design conducted at the Autonomous Community of Madrid. A Research Team participated in the study; the team was formed by experts on research methodology and nursing methodology. The study consisted of three phases: a list was prepared first with 80 NIC Nursing interventions, selected by consensus; secondly, an ad hoc survey was designed, containing the 80 NICs with different answer options based on the frequency they were carried out in daily practice; and the third phase was a cross-sectional study targeted to Nursing professionals working at hospitalization units for adult patients from the 10 hospitals involved. The survey was sent by e-mail. Descriptive analysis was conducted. Results: the study included 427 nurses; their mean years of seniority (standard deviation) was 14 (7.74). The most prevalent NICs that were done more than three times per day were: medication administration (n= 294; 68.9%); medication monitoring (n= 285; 66.7%); oral medication administration (n= 282; 66%); pain management (n= 280; 65.6%); active listening (277; 64.9%); administration of analgesics (272; 63.9%); change of position (n= 262; 61.4%), among others. Conclusions: the interventions most frequently carried out were identified, as a first line of work targeted to obtaining more information on interventions and times of performance, which will help to improve the management of human resources based on patient needs.
Databáze: OpenAIRE