Nursing Diagnoses as Predictors of Hospital Length of Stay: A Prospective Observational Study

Antonello Cocchieri, Maurizio Zega, Fabio D'Agostino, Ercole Vellone, John Welton, Massimo Maurici, Barbara Polistena, Federico Spandonaro, Rosaria Alvaro, Gianfranco Sanson

Risultato della ricerca: Contributo in rivistaArticolo in rivista

7 Citazioni (Scopus)

Abstract

Purpose: To investigate whether the number of nursing diagnoses on hospital admission is an independent predictor of the hospital length of stay. Design: A prospective observational study was carried out. A sample of 2,190 patients consecutively admitted (from July to December 2014) in four inpatient units (two medical, two surgical) of a 1,547-bed university hospital were enrolled for the study. Methods: Data were collected from a clinical nursing information system and the hospital discharge register. Two regression analyses were performed to investigate if the number of nursing diagnoses on hospital admission was an independent predictor of length of stay and length of stay deviation after controlling for patients’ sociodemographic characteristics (age, gender), clinical variables (disease groupers, disease severity morbidity indexes), and organizational hospital variables (admitting inpatient unit, modality of admission). Findings: The number of nursing diagnoses was shown to be an independent predictor of both the length of stay (β =.15; p <.001) and the length of stay deviation (β =.19; p <.001). Conclusions: The number of nursing diagnoses is a strong independent predictor of an effective hospital length of stay and of a length of stay longer than expected. Clinical Relevance: The systematic inclusion of standard nursing care data in electronic health records can improve the predictive ability on hospital outcomes and describe the patient complexity more comprehensively, improving hospital management efficiency.
Lingua originaleEnglish
pagine (da-a)96-105
Numero di pagine10
RivistaJournal of Nursing Scholarship
Volume51
DOI
Stato di pubblicazionePubblicato - 2019

Keywords

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Child
  • Diagnosis-related groups
  • Electronic Health Records
  • Female
  • Hospital Mortality
  • Hospitalization
  • Hospitals, University
  • Humans
  • Length of Stay
  • Male
  • Middle Aged
  • Nursing Diagnosis
  • Patient Admission
  • Patient Discharge
  • Prospective Studies
  • Regression Analysis
  • Severity of Illness Index
  • Young Adult
  • hospital length of stay
  • nursing diagnosis
  • observational study
  • outcome
  • regression analysis

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