Cargando…

Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology

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 quali...

Descripción completa

Detalles Bibliográficos
Autores principales: Sermeus, Walter, Aiken, Linda H, Van den Heede, Koen, Rafferty, Anne Marie, Griffiths, Peter, Moreno-Casbas, Maria Teresa, Busse, Reinhard, Lindqvist, Rikard, Scott, Anne P, Bruyneel, Luk, Brzostek, Tomasz, Kinnunen, Juha, Schubert, Maria, Schoonhoven, Lisette, Zikos, Dimitrios
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3108324/
https://www.ncbi.nlm.nih.gov/pubmed/21501487
http://dx.doi.org/10.1186/1472-6955-10-6
_version_ 1782205306627948544
author Sermeus, Walter
Aiken, Linda H
Van den Heede, Koen
Rafferty, Anne Marie
Griffiths, Peter
Moreno-Casbas, Maria Teresa
Busse, Reinhard
Lindqvist, Rikard
Scott, Anne P
Bruyneel, Luk
Brzostek, Tomasz
Kinnunen, Juha
Schubert, Maria
Schoonhoven, Lisette
Zikos, Dimitrios
author_facet Sermeus, Walter
Aiken, Linda H
Van den Heede, Koen
Rafferty, Anne Marie
Griffiths, Peter
Moreno-Casbas, Maria Teresa
Busse, Reinhard
Lindqvist, Rikard
Scott, Anne P
Bruyneel, Luk
Brzostek, Tomasz
Kinnunen, Juha
Schubert, Maria
Schoonhoven, Lisette
Zikos, Dimitrios
author_sort Sermeus, Walter
collection PubMed
description 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/DESIGN: 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. DISCUSSION: 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.
format Online
Article
Text
id pubmed-3108324
institution National Center for Biotechnology Information
language English
publishDate 2011
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-31083242011-06-07 Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology Sermeus, Walter Aiken, Linda H Van den Heede, Koen Rafferty, Anne Marie Griffiths, Peter Moreno-Casbas, Maria Teresa Busse, Reinhard Lindqvist, Rikard Scott, Anne P Bruyneel, Luk Brzostek, Tomasz Kinnunen, Juha Schubert, Maria Schoonhoven, Lisette Zikos, Dimitrios BMC Nurs Study Protocol 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/DESIGN: 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. DISCUSSION: 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. BioMed Central 2011-04-18 /pmc/articles/PMC3108324/ /pubmed/21501487 http://dx.doi.org/10.1186/1472-6955-10-6 Text en Copyright ©2011 Sermeus et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Study Protocol
Sermeus, Walter
Aiken, Linda H
Van den Heede, Koen
Rafferty, Anne Marie
Griffiths, Peter
Moreno-Casbas, Maria Teresa
Busse, Reinhard
Lindqvist, Rikard
Scott, Anne P
Bruyneel, Luk
Brzostek, Tomasz
Kinnunen, Juha
Schubert, Maria
Schoonhoven, Lisette
Zikos, Dimitrios
Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology
title Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology
title_full Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology
title_fullStr Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology
title_full_unstemmed Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology
title_short Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology
title_sort nurse forecasting in europe (rn4cast): rationale, design and methodology
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3108324/
https://www.ncbi.nlm.nih.gov/pubmed/21501487
http://dx.doi.org/10.1186/1472-6955-10-6
work_keys_str_mv AT sermeuswalter nurseforecastingineuropern4castrationaledesignandmethodology
AT aikenlindah nurseforecastingineuropern4castrationaledesignandmethodology
AT vandenheedekoen nurseforecastingineuropern4castrationaledesignandmethodology
AT raffertyannemarie nurseforecastingineuropern4castrationaledesignandmethodology
AT griffithspeter nurseforecastingineuropern4castrationaledesignandmethodology
AT morenocasbasmariateresa nurseforecastingineuropern4castrationaledesignandmethodology
AT bussereinhard nurseforecastingineuropern4castrationaledesignandmethodology
AT lindqvistrikard nurseforecastingineuropern4castrationaledesignandmethodology
AT scottannep nurseforecastingineuropern4castrationaledesignandmethodology
AT bruyneelluk nurseforecastingineuropern4castrationaledesignandmethodology
AT brzostektomasz nurseforecastingineuropern4castrationaledesignandmethodology
AT kinnunenjuha nurseforecastingineuropern4castrationaledesignandmethodology
AT schubertmaria nurseforecastingineuropern4castrationaledesignandmethodology
AT schoonhovenlisette nurseforecastingineuropern4castrationaledesignandmethodology
AT zikosdimitrios nurseforecastingineuropern4castrationaledesignandmethodology
AT nurseforecastingineuropern4castrationaledesignandmethodology