Alvisa Palese1, Eva Marini2, Annamaria Guarnier3, Paolo Barelli3, Paola Zambiasi3, Elisabetta Allegrini4, Letizia Bazoli5, Paola Casson6, Meri Marin7, Marisa Padovan8, Michele Picogna9, Patrizia Taddia10, Paolo Chiari11, Daniele Salmaso12, Oliva Marognolli13, Federica Canzan14, Elisa Ambrosi14, Luisa Saiani14, Luca Grassetti2. 1. Nursing Science, Udine University, Udine, Italy. alvisa.palese@uniud.it. 2. Udine University, Udine, Italy. 3. Azienda provinciale per i Servizi Sanitari, Trento, Italy. 4. Azienda Ospedaliero-Universitaria, Verona, Italy. 5. Fondazione Poliambulanza, Brescia, Italy. 6. Azienda per i Servizi Sanitari, Treviso, Italy. 7. Azienda per i Servizi Sanitari, Gorizia, Italy. 8. Azienda per i Servizi Sanitari, Vicenza, Italy. 9. Azienda per i Servizi Sanitari, Udine, Italy. 10. Azienda Ospedaliera-Universitaria, Bologna, Italy. 11. Nursing Science, Bologna University, Bologna, Italy. 12. Fondazione Zancan, Padua, Italy. 13. Nursing Students' Clinical Placements, Verona University, Verona, Italy. 14. Verona University, Verona, Italy.
Abstract
RATIONALE: There is growing interest in validating tools aimed at supporting the clinical decision-making process and research. However, an increased bureaucratization of clinical practice and redundancies in the measures collected have been reported by clinicians. Redundancies in clinical assessments affect negatively both patients and nurses. METHODS: To validate a meta-tool measuring the risks/problems currently estimated by multiple tools used in daily practice. A secondary analysis of a database was performed, using a cross-validation and a longitudinal study designs. In total, 1464 patients admitted to 12 medical units in 2012 were assessed at admission with the Brass, Barthel, Conley and Braden tools. Pertinent outcomes such as the occurrence of post-discharge need for resources and functional decline at discharge, as well as falls and pressure sores, were measured. Explorative factor analysis of each tool, inter-tool correlations and a conceptual evaluation of the redundant/similar items across tools were performed. Therefore, the validation of the meta-tool was performed through explorative factor analysis, confirmatory factor analysis and the structural equation model to establish the ability of the meta-tool to predict the outcomes estimated by the original tools. RESULTS: High correlations between the tools have emerged (from r 0.428 to 0.867) with a common variance from 18.3% to 75.1%. Through a conceptual evaluation and explorative factor analysis, the items were reduced from 42 to 20, and the three factors that emerged were confirmed by confirmatory factor analysis. According to the structural equation model results, two out of three emerged factors predicted the outcomes. CONCLUSIONS: From the initial 42 items, the meta-tool is composed of 20 items capable of predicting the outcomes as with the original tools.
RCT Entities:
RATIONALE: There is growing interest in validating tools aimed at supporting the clinical decision-making process and research. However, an increased bureaucratization of clinical practice and redundancies in the measures collected have been reported by clinicians. Redundancies in clinical assessments affect negatively both patients and nurses. METHODS: To validate a meta-tool measuring the risks/problems currently estimated by multiple tools used in daily practice. A secondary analysis of a database was performed, using a cross-validation and a longitudinal study designs. In total, 1464 patients admitted to 12 medical units in 2012 were assessed at admission with the Brass, Barthel, Conley and Braden tools. Pertinent outcomes such as the occurrence of post-discharge need for resources and functional decline at discharge, as well as falls and pressure sores, were measured. Explorative factor analysis of each tool, inter-tool correlations and a conceptual evaluation of the redundant/similar items across tools were performed. Therefore, the validation of the meta-tool was performed through explorative factor analysis, confirmatory factor analysis and the structural equation model to establish the ability of the meta-tool to predict the outcomes estimated by the original tools. RESULTS: High correlations between the tools have emerged (from r 0.428 to 0.867) with a common variance from 18.3% to 75.1%. Through a conceptual evaluation and explorative factor analysis, the items were reduced from 42 to 20, and the three factors that emerged were confirmed by confirmatory factor analysis. According to the structural equation model results, two out of three emerged factors predicted the outcomes. CONCLUSIONS: From the initial 42 items, the meta-tool is composed of 20 items capable of predicting the outcomes as with the original tools.