Aims: To describe the prevalence of nursing diagnoses on admission among inpatient units and medical diagnoses and to analyse the relationship of nursing diagnoses to patient characteristics and hospital outcomes. Background: Nursing diagnoses classify patients according to nursing dependency and can be a measure of nursing complexity. Knowledge regarding the prevalence of nursing diagnoses on admission and their relationship with hospital outcomes is lacking. Design: Prospective observational study. Methods: Data were collected for 6 months in 2014 in four inpatient units of an Italian hospital using a nursing information system and the hospital discharge register. Nursing diagnoses with prevalence higher or equal to 20% were considered as ‘high frequency.’ Nursing diagnoses with statistically significant relationships with either higher mortality or length of stay were considered as ‘high risk.’ The high-frequency/high-risk category of nursing diagnoses was identified. Results: The sample included 2283 patients. A mean of 4·5 nursing diagnoses per patient was identified; this number showed a statistically significant difference among inpatient units and medical diagnoses. Six nursing diagnoses were classified as high frequency/high risk. Nursing diagnoses were not correlated with patient gender and age. A statistically significant perfect linear association (Spearman's correlation coefficient) was observed between the number of nursing diagnoses and both the length of stay and the mortality rate. Conclusion: Nursing complexity, as described by nursing diagnoses, was shown to be associated with length of stay and mortality. These results should be confirmed after considering other variables through multivariate analyses. The concept of high-frequency/high-risk nursing diagnoses should be expanded in further studies.
D'Agostino, F., Sanson, G., Cocchieri, A., Vellone, E., Welton, J., Maurici, M., Alvaro, R., Zega, M., Prevalence of nursing diagnoses as a measure of nursing complexity in a hospital setting, <<JOURNAL OF ADVANCED NURSING>>, 2017; 73 (9): 2129-2142. [doi:10.1111/jan.13285] [http://hdl.handle.net/10807/165316]
Prevalence of nursing diagnoses as a measure of nursing complexity in a hospital setting
Cocchieri, Antonello;Zega, Maurizio
2017
Abstract
Aims: To describe the prevalence of nursing diagnoses on admission among inpatient units and medical diagnoses and to analyse the relationship of nursing diagnoses to patient characteristics and hospital outcomes. Background: Nursing diagnoses classify patients according to nursing dependency and can be a measure of nursing complexity. Knowledge regarding the prevalence of nursing diagnoses on admission and their relationship with hospital outcomes is lacking. Design: Prospective observational study. Methods: Data were collected for 6 months in 2014 in four inpatient units of an Italian hospital using a nursing information system and the hospital discharge register. Nursing diagnoses with prevalence higher or equal to 20% were considered as ‘high frequency.’ Nursing diagnoses with statistically significant relationships with either higher mortality or length of stay were considered as ‘high risk.’ The high-frequency/high-risk category of nursing diagnoses was identified. Results: The sample included 2283 patients. A mean of 4·5 nursing diagnoses per patient was identified; this number showed a statistically significant difference among inpatient units and medical diagnoses. Six nursing diagnoses were classified as high frequency/high risk. Nursing diagnoses were not correlated with patient gender and age. A statistically significant perfect linear association (Spearman's correlation coefficient) was observed between the number of nursing diagnoses and both the length of stay and the mortality rate. Conclusion: Nursing complexity, as described by nursing diagnoses, was shown to be associated with length of stay and mortality. These results should be confirmed after considering other variables through multivariate analyses. The concept of high-frequency/high-risk nursing diagnoses should be expanded in further studies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.