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

被引：264

作者：

Sermeus W. ^{[1
]}

Aiken L.H. ^{[2
]}

Van den Heede K. ^{[1
]}

Rafferty A.M. ^{[3
]}

Griffiths P. ^{[4
]}

Moreno-Casbas M.T. ^{[5
]}

Busse R. ^{[6
]}

Lindqvist R. ^{[7
]}

Scott A.P. ^{[8
]}

Bruyneel L. ^{[1
]}

Brzostek T. ^{[9
]}

Kinnunen J. ^{[10
]}

Schubert M. ^{[11
]}

Schoonhoven L. ^{[12
]}

Zikos D. ^{[13
]}

机构：

[1] Center for Health Services and Nursing Research, Katholieke Universiteit Leuven, 3000 Leuven

[2] Center for Health Outcomes and Policy Research, University of Pennsylvania, Philadelphia PA 19104-4217, 418 Curie Blvd. Claire M. Fagin Hall

[3] Florence Nightingale School of Nursing and Midwifery, King's College London, James Clerk Maxwell Building, London SE1 8WA

[4] School of Health Sciences, University of Southampton, Southampton 17 1BJ, Building 67, Highfield Campus

[5] National Spanish Research Unit, Instituto de Salud Carlos III. Ministry of Science and Innovation, 28029 Madrid, C/Monforte de Lemos

[6] Department of Health Care Management, WHO Collaborating Centre for Health Systems Research and Management, Technische Universität Berlin, 10623 Berlin

[7] Department of Learning Informatics, Management and Ethics, Karolinska Institutet

[8] School of Nursing, Dublin City University

[9] Department of Internal Diseases and Community Nursing, Jagiellonian University Medical College, 31-501 Krakow

[10] Department of Health Policy and Management, University of Eastern Finland, 70211 Kuopio

[11] Institute of Nursing Science, University of Basel, 4056 Basel

[12] Scientific Institute for Quality of Healthcare, UMC St Radboud, 6500 HB Nijmegen, Postbus 9101

[13] Laboratory of Health Informatics, Faculty of Nursing, National and Kapodistrian University of Athens, 11527 Athens

来源：

BMC Nursing | / 10卷 / 1期

关键词：

Patient Level Data; Workforce Planning; Nursing Unit; Nursing Workforce; Nurse Staffing Level;

D O I：

10.1186/1472-6955-10-6

中图分类号：

学科分类号：

摘要：

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. © 2011 Sermeus et al; licensee BioMed Central Ltd.

引用

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