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

Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology
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 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.
1472-6955
Sermeus, Walter
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Aiken, Linda H.
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Heede, Koen Van den
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Rafferty, Anne Marie
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Griffiths, Peter
ac7afec1-7d72-4b83-b016-3a43e245265b
Moreno-Casbas, Maria Teresa
b0c80237-c1c2-4cfc-bb99-f9440407fdee
Busse, Reinhard
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Tishelman, Carol
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Scott, Anne
06ed79cc-e1da-44cf-a687-e915732f28ed
Bruyneel, Luk
b1dccbf8-34ee-4b11-b698-790131e1abb0
Brzostek, Tomasz
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Kinnunen, Juha
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Schubert, Maria
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Schoonhoven, Lisette
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Zikos, Dimitris
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RN4CAST Consortium
Sermeus, Walter
42465ab5-e333-4fe8-9a80-c55f6c15a3ab
Aiken, Linda H.
6110096b-bab9-41a7-89f4-d7043011d6d9
Heede, Koen Van den
29857a1a-08a9-4b67-aba6-017f4b6111ad
Rafferty, Anne Marie
d82c2661-2b39-447c-b975-c42834480975
Griffiths, Peter
ac7afec1-7d72-4b83-b016-3a43e245265b
Moreno-Casbas, Maria Teresa
b0c80237-c1c2-4cfc-bb99-f9440407fdee
Busse, Reinhard
a46419f0-8c6f-417e-8b05-175567613dff
Tishelman, Carol
11d9dd11-f992-48d7-b8ef-a9f428a809d6
Scott, Anne
06ed79cc-e1da-44cf-a687-e915732f28ed
Bruyneel, Luk
b1dccbf8-34ee-4b11-b698-790131e1abb0
Brzostek, Tomasz
83d92b14-906e-4c82-bc88-325d856cd26c
Kinnunen, Juha
c0b9709a-5bbd-4d3c-96b4-329f4cad9972
Schubert, Maria
2f74e6d3-5a72-42fd-a48e-24c9ef16c0db
Schoonhoven, Lisette
93f67b5c-d879-45b9-aad1-0e1dba6c7ba3
Zikos, Dimitris
3f4ce41e-fac4-4bfd-9dae-9b10813519f4

Sermeus, Walter, Aiken, Linda H., Heede, Koen Van den, Rafferty, Anne Marie, Griffiths, Peter, Moreno-Casbas, Maria Teresa, Busse, Reinhard, Tishelman, Carol, Scott, Anne, Bruyneel, Luk, Brzostek, Tomasz, Kinnunen, Juha, Schubert, Maria, Schoonhoven, Lisette and Zikos, Dimitris , RN4CAST Consortium (2011) Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology. BMC Nursing. (Submitted)

Record type: Article

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/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.

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More information

Submitted date: 2011

Identifiers

Local EPrints ID: 177883
URI: http://eprints.soton.ac.uk/id/eprint/177883
ISSN: 1472-6955
PURE UUID: 39595680-a960-4bb6-857a-c36d2b7b56b1
ORCID for Peter Griffiths: ORCID iD orcid.org/0000-0003-2439-2857

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Date deposited: 21 Mar 2011 14:33
Last modified: 23 Jul 2022 02:02

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Contributors

Author: Walter Sermeus
Author: Linda H. Aiken
Author: Koen Van den Heede
Author: Anne Marie Rafferty
Author: Peter Griffiths ORCID iD
Author: Maria Teresa Moreno-Casbas
Author: Reinhard Busse
Author: Carol Tishelman
Author: Anne Scott
Author: Luk Bruyneel
Author: Tomasz Brzostek
Author: Juha Kinnunen
Author: Maria Schubert
Author: Lisette Schoonhoven
Author: Dimitris Zikos
Corporate Author: RN4CAST Consortium

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