STUDY PROTOCOL Open Access Nurse forecasting in Europe (RN4CAST): Rationale, design and methodology Walter Sermeus 1 , Linda H Aiken 2 , Koen Van den Heede 1* , Anne Marie Rafferty 3 , Peter Griffiths 4 , Maria Teresa Moreno-Casbas 5 , Reinhard Busse 6 , Rikard Lindqvist 7 , Anne P Scott 8 , Luk Bruyneel 1 , Tomasz Brzostek 9 , Juha Kinnunen 10 , Maria Schubert 11 , Lisette Schoonhoven 12 , Dimitrios Zikos 13 and RN4CAST consortium 13 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. Background All countries, rich and poor, have numeric, skill, and geographic imbalances in their healthcare and nursing workforce [1] and are lacking an adequate nurse work- force to meet projected future requirements for care. This global nurse shortage is remarkable in light of the highly reported variability in nurse density (number of nurses per 1000 inhabitants) across countries. In Eur- ope, for example, the highest (Ireland: 14.8) nurse den- sity is nearly 4 times higher than the lowest nurse density (Greece: 3.8) [2]. The observed variation in nurse density seems, apparently, to be independent from the reported shortages of nursing personnel across Eur- opean countries. This can, possibly, be explained by the definition and measurement of shortages. Nursing shortages on the country level are mostly viewed in rela- tion to that country’s own historical staffing levels and resources [3]. Driven by ageing populations, demand for * Correspondence: koen.vandenheede@med.kuleuven.be 1 Center for Health Services and Nursing Research, Katholieke Universiteit Leuven, Kapucijnenvoer 35/4, 3000 Leuven, Belgium Full list of author information is available at the end of the article Sermeus et al. BMC Nursing 2011, 10:6 http://www.biomedcentral.com/1472-6955/10/6 © 2011 Sermeus et al; licensee BioMed Central Ltd. 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.