title: [Assessing the trend in the aging of the nursing staff at two hospitals of the Friuli Venezia Giulia region: application of a deterministic mathematical model].
abstract: BACKGROUND
  The aging of the nursing workforce is a phenomenon that several industrialized countries has been facing for at least a decade. In Italy, for the period between 2011 and 2021, the issue associated with the nursing workforce will not be one of shortage but rather one of aging.
  
  
  OBJECTIVE
  The main objective of this study was to estimate the employed nurse population aging trends for the period 2009-2035 in two Teaching Hospitals (TH1 and TH2) located in the North of Italy.
  
  
  METHODS
  A deterministic mathematical model has been developed in order to obtain aging projections for the nursing workforce from 2009 until 2035.
  
  
  RESULTS
  Within the next six years, the aging trend of nurse populations, with respect to 2008, at the TH 1 and 2 will show a steady increase of nurses aged over 45; specifically, a 29.4% vs. 34.1% increase and a 21.6% vs. 41.4% respectively. It is hypothesized that the TH 1 will have the highest proportion of nurses aged over 45 in 2014, whereas it is estimated that for the TH 2 this trend will continue until 2021 when the proportion of nurses aged over 45 will make up 48.8% out of the nurse population.
  
  
  CONCLUSIONS
  The trend may lead to an increase in the number of experienced nurses; however, such a trend should be looked at with concern, with respect to the physical unsuitability. Nurses aged over 45 represent 20% of the workforce at both TH. Conclusions/implications for management and research. If the trend predicted by the model were to occur in the coming years, the problem of nursing workforce ageing will have to be addressed because it involves different expectations but also the perception of different work skills. The nursing direction is called to test new strategies for managing the staff and the career of nurses will also need to be redesigned, because contract law looks primarily at the initial stage of working life (specializations, university education, career opportunities) neglecting the final one (from the 50th year of age to retirement).
authors.affiliation: Azienda Ospedaliero-Universitaria Santa Maria della Misercordia, Udine.
authors.forename: Ilario
authors.initials: I
authors.lastname: Guardini
authors.forename: Laura
authors.initials: L
authors.lastname: Deroma
authors.forename: Daniele
authors.initials: D
authors.lastname: Salmaso
authors.forename: Alvisa
authors.initials: A
authors.lastname: Palese
mesh_terms: D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D000375:Aging; D006301:Health Services Needs and Demand / Q000639:trends; D006784:Hospitals, Teaching / Q000706:statistics & numerical data / Q000639:trends*; D006801:Humans; D007558:Italy; D015233:Models, Statistical; D008962:Models, Theoretical; D009741:Nursing Staff, Hospital / Q000600:supply & distribution / Q000639:trends*; D010560:Personnel Selection / Q000639:trends; D010563:Personnel Turnover / Q000639:trends; D012179:Retirement / Q000639:trends; D012307:Risk Factors; D013997:Time Factors