title: Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology.
abstract: BACKGROUND
  Current human resources planning models in nursing are unreliable and ineffective as they consider volumes, but ignore effects on quality in patient care. The project RN4CAST aims innovative forecasting methods by addressing not only volumes, but quality of nursing staff as well as quality of patient care.
  
  
  METHODS
  A multi-country, multilevel cross-sectional design is used to obtain important unmeasured factors in forecasting models including how features of hospital work environments impact on nurse recruitment, retention and patient outcomes. In each of the 12 participating European countries, at least 30 general acute hospitals were sampled. Data are gathered via four data sources (nurse, patient and organizational surveys and via routinely collected hospital discharge data). All staff nurses of a random selection of medical and surgical units (at least 2 per hospital) were surveyed. The nurse survey has the purpose to measure the experiences of nurses on their job (e.g. job satisfaction, burnout) as well as to allow the creation of aggregated hospital level measures of staffing and working conditions. The patient survey is organized in a sub-sample of countries and hospitals using a one-day census approach to measure the patient experiences with medical and nursing care. In addition to conducting a patient survey, hospital discharge abstract datasets will be used to calculate additional patient outcomes like in-hospital mortality and failure-to-rescue. Via the organizational survey, information about the organizational profile (e.g. bed size, types of technology available, teaching status) is collected to control the analyses for institutional differences.This information will be linked via common identifiers and the relationships between different aspects of the nursing work environment and patient and nurse outcomes will be studied by using multilevel regression type analyses. These results will be used to simulate the impact of changing different aspects of the nursing work environment on quality of care and satisfaction of the nursing workforce.
  
  
  CONCLUSIONS
  RN4CAST is one of the largest nurse workforce studies ever conducted in Europe, will add to accuracy of forecasting models and generate new approaches to more effective management of nursing resources in Europe.
authors.affiliation: Center for Health Services and Nursing Research, Katholieke Universiteit Leuven, Kapucijnenvoer 35/4, 3000 Leuven, Belgium. koen.vandenheede@med.kuleuven.be.
authors.forename: Walter
authors.initials: W
authors.lastname: Sermeus
authors.forename: Linda H
authors.initials: LH
authors.lastname: Aiken
authors.forename: Koen
authors.initials: K
authors.lastname: Van den Heede
authors.forename: Anne Marie
authors.initials: AM
authors.lastname: Rafferty
authors.forename: Peter
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authors.lastname: Griffiths
authors.forename: Maria Teresa
authors.initials: MT
authors.lastname: Moreno-Casbas
authors.forename: Reinhard
authors.initials: R
authors.lastname: Busse
authors.forename: Rikard
authors.initials: R
authors.lastname: Lindqvist
authors.forename: Anne P
authors.initials: AP
authors.lastname: Scott
authors.forename: Luk
authors.initials: L
authors.lastname: Bruyneel
authors.forename: Tomasz
authors.initials: T
authors.lastname: Brzostek
authors.forename: Juha
authors.initials: J
authors.lastname: Kinnunen
authors.forename: Maria
authors.initials: M
authors.lastname: Schubert
authors.forename: Lisette
authors.initials: L
authors.lastname: Schoonhoven
authors.forename: Dimitrios
authors.initials: D
authors.lastname: Zikos