title: Prevalence of nursing diagnoses as a measure of nursing complexity in a hospital setting.
abstract: OBJECTIVE
  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.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Biomedicine and Prevention, University of Rome Tor Vergata, Italy.
authors.forename: Fabio
authors.identifier: http://orcid.org/0000-0002-4641-604X
authors.initials: F
authors.lastname: D'Agostino
authors.affiliation: Department of Biomedicine and Prevention, University of Rome Tor Vergata, Italy.
authors.forename: Gianfranco
authors.identifier: http://orcid.org/0000-0001-8319-635X
authors.initials: G
authors.lastname: Sanson
authors.affiliation: Catholic University of the Sacred Heart, Rome, Italy.
authors.forename: Antonello
authors.initials: A
authors.lastname: Cocchieri
authors.affiliation: Department of Biomedicine and Prevention, University of Rome Tor Vergata, Italy.
authors.forename: Ercole
authors.initials: E
authors.lastname: Vellone
authors.affiliation: University of Colorado College of Nursing, Aurora, CO, USA.
authors.forename: John
authors.initials: J
authors.lastname: Welton
authors.affiliation: Department of Biomedicine and Prevention, University of Rome Tor Vergata, Italy.
authors.forename: Massimo
authors.initials: M
authors.lastname: Maurici
authors.affiliation: Department of Biomedicine and Prevention, University of Rome Tor Vergata, Italy.
authors.forename: Rosaria
authors.initials: R
authors.lastname: Alvaro
authors.affiliation: University Hospital Agostino Gemelli, Rome, Italy.
authors.forename: Maurizio
authors.initials: M
authors.lastname: Zega
mesh_terms: D000328:Adult; D005260:Female; D017052:Hospital Mortality; D006801:Humans; D007558:Italy; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D009733:Nursing Diagnosis / Q000706:statistics & numerical data*; D010343:Patient Admission / Q000706:statistics & numerical data*; D010351:Patient Discharge / Q000706:statistics & numerical data*; D015995:Prevalence; D011446:Prospective Studies
keywords: correlation; hospital outcomes; nursing complexity; nursing diagnosis; patient outcome; prevalence