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.

Twenty-four hour nursing care involves shift work including 12-h shifts. England is unusual in deploying a mix of shift patterns. International evidence on the effects of such shifts is growing. A secondary analysis of data collected in England exploring outcomes with 12-h shifts examined the association between shift length, job satisfaction, scheduling flexibility, care quality, patient safety, and care left undone. Data were collected from a questionnaire survey of nurses in a sample of English hospitals, conducted as part of the RN4CAST study, an EU 7th Framework funded study. The sample comprised 31 NHS acute hospital Trusts from 401 wards, in 46 acute hospital sites. Descriptive analysis included frequencies, percentages and mean scores by shift length, working beyond contracted hours and day or night shift. Multi-level regression models established statistical associations between shift length and nurse self-reported measures. Seventy-four percent (1898) of nurses worked a day shift and 26% (670) a night shift. Most Trusts had a mixture of shifts lengths. Self-reported quality of care was higher amongst nurses working ≤8 h (15.9%) compared to those working longer hours (20.0 to 21.1%). The odds of poor quality care were 1.64 times higher for nurses working ≥12 h (OR = 1.64, 95% CI 1.18–2.28, p = 0.003). Mean ‘care left undone’ scores varied by shift length: 3.85 (≤8 h), 3.72 (8.01–10.00 h), 3.80 (10.01–11.99 h) and were highest amongst those working ≥12 h (4.23) (p < 0.001). The rate of care left undone was 1.13 times higher for nurses working ≥12 h (RR = 1.13, 95% CI 1.06–1.20, p < 0.001). Job dissatisfaction was higher the longer the shift length: 42.9% (≥12 h (OR = 1.51, 95% CI 1.17–1.95, p = .001); 35.1% (≤8 h) 45.0% (8.01–10.00 h), 39.5% (10.01–11.99 h). Our findings add to the growing international body of evidence reporting that ≥12 shifts are associated with poor ratings of quality of care and higher rates of care left undone. Future research should focus on how 12-h shifts can be optimised to minimise potential risks.

Medication administration errors may contribute to patient mortality, thus additional understanding of such incidents is required. To analyse medication administration errors reported in acute care resulting in death, to identify the drugs concerned, and to describe medication administration error characteristics (location of error, error type, patient's age) by drug group. Medication administration errors reported in acute care in 2007 ̶ 2016 (n = 517,384) were obtained from the National Reporting and Learning System for England and Wales. Incidents reported as resulting in death (n = 229) were analysed. Drugs were classified by two researchers using the British National Formulary. Drug categories were described by medication administration errors' year, location, patient age, and error category based on the incidents' original classification. Errors were most often reported on wards (66.4%, n = 152), and in patients aged over 75 years (41.5%, n = 95). The most common error category was omitted medicine or ingredient (31.4%, n = 72); most common drug groups were cardiovascular (20.1%, n = 46) and nervous system (10.0%, n = 23). Most errors in patients under 12 years concerned drugs to treat infection; cardiovascular drugs were most common among other age groups. In order to prevent these most serious of medication administration errors, interventions should focus on avoiding dose omissions, and administration of drugs for patients over 75 years old, as well as safe administration of parenteral anticoagulants and antibacterial drugs.