title: Impact of nursing diagnoses on patient and organisational outcomes: a systematic literature review.
abstract: OBJECTIVE
  To investigate the impact of nursing diagnoses on patient and organisational outcomes in any field of health care where nurses are involved.
  
  
  BACKGROUND
  In healthcare systems, descriptions of patient complexity and outcomes and payment criteria are primarily based on medical diagnoses and procedures. Other aspects of patient care are rarely considered. Nursing diagnoses are believed to be related to healthcare outcomes, but comprehensive evidence for this association is missing.
  
  
  METHODS
  Systematic literature review.
  
  
  METHODS
  The search was conducted in PubMed, CINAHL and Scopus databases without year or language limitations. The studies were categorised according to their methodological quality (low, good or high) and classified based on their levels of evidence on a scale of 1 (strongest evidence) to 5 (weakest evidence).
  
  
  RESULTS
  Seventeen of 3426 potentially relevant studies met the eligibility criteria. Eleven studies were classified as low, five as good and one as high quality. The levels of evidence were rated as 2 for one study, three for two studies, four for nine studies and five for five studies. Nursing diagnoses were found to predict patient (quality of life, mortality) and organisational (length of hospital stay, hospital charges, amount of nursing care, discharge dispositions) outcomes. Patient care plans based on nursing diagnoses improved sleep quality, quality of life and glycaemic control. When added to information from disease-based classification systems (e.g. diagnosis-related groups), nursing diagnoses improved the predictions of the above outcomes.
  
  
  CONCLUSIONS
  Nursing diagnoses have a great potential to predict patient and organisational outcomes. High-quality research is required to better investigate the existence and strength of these relationships.
  
  
  CONCLUSIONS
  The systematic use of nursing diagnoses in clinical practice, as well as the sharing of high-quality nursing data in large databases, may provide a considerable boost to the contribution of nursing to healthcare outcomes.
authors.affiliation: Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
authors.forename: Gianfranco
authors.initials: G
authors.lastname: Sanson
authors.affiliation: Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
authors.forename: Ercole
authors.initials: E
authors.lastname: Vellone
authors.affiliation: Department of Nursing Science, University of Eastern Finland, Kuopio, Finland.
authors.forename: Mari
authors.initials: M
authors.lastname: Kangasniemi
authors.affiliation: Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
authors.forename: Rosaria
authors.initials: R
authors.lastname: Alvaro
authors.affiliation: Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.
authors.forename: Fabio
authors.initials: F
authors.lastname: D'Agostino
mesh_terms: D003695:Delivery of Health Care / Q000458:organization & administration; D006801:Humans; D009733:Nursing Diagnosis; D015399:Nursing Research; D010043:Outcome and Process Assessment, Health Care; D011788:Quality of Life
keywords: nursing data; nursing diagnosis; outcome; systematic review