title: Nurse staffing levels and outcomes - mining the UK national data sets for insight.
abstract: Purpose Despite the generation of mass data by the nursing workforce, determining the impact of the contribution to patient safety remains challenging. Several cross-sectional studies have indicated a relationship between staffing and safety. The purpose of this paper is to uncover possible associations and explore if a deeper understanding of relationships between staffing and other factors such as safety could be revealed within routinely collected national data sets. Design/methodology/approach Two longitudinal routinely collected data sets consisting of 30 years of UK nurse staffing data and seven years of National Health Service (NHS) benchmark data such as survey results, safety and other indicators were used. A correlation matrix was built and a linear correlation operation was applied (Pearson product-moment correlation coefficient). Findings A number of associations were revealed within both the UK staffing data set and the NHS benchmarking data set. However, the challenges of using these data sets soon became apparent. Practical implications Staff time and effort are required to collect these data. The limitations of these data sets include inconsistent data collection and quality. The mode of data collection and the itemset collected should be reviewed to generate a data set with robust clinical application. Originality/value This paper revealed that relationships are likely to be complex and non-linear; however, the main contribution of the paper is the identification of the limitations of routinely collected data. Much time and effort is expended in collecting this data; however, its validity, usefulness and method of routine national data collection appear to require re-examination.
authors.affiliation: School of Health and Social Care, London South Bank University , London, UK.
authors.forename: Alison
authors.initials: A
authors.lastname: Leary
authors.affiliation: Centre for Workforce Intelligence, Mouchel Management Consulting Limited, London, UK.
authors.forename: Barbara
authors.initials: B
authors.lastname: Tomai
authors.affiliation: Centre for Workforce Intelligence, Mouchel Management Consulting Limited, London, UK.
authors.forename: Adrian
authors.initials: A
authors.lastname: Swift
authors.affiliation: Centre for Workforce Intelligence, Mouchel Management Consulting Limited, London, UK.
authors.forename: Andrew
authors.initials: A
authors.lastname: Woodward
authors.affiliation: Hurst Research Ltd, Mansfield, UK.
authors.forename: Keith
authors.initials: K
authors.lastname: Hurst
mesh_terms: D001509:Bed Occupancy; D019985:Benchmarking; D003365:Costs and Cost Analysis; D003430:Cross-Sectional Studies; D003625:Data Collection; D006801:Humans; D009741:Nursing Staff, Hospital / Q000458:organization & administration*; D061214:Patient Safety; D010561:Personnel Staffing and Scheduling / Q000458:organization & administration*; D019984:Quality Indicators, Health Care; D011787:Quality of Health Care / Q000458:organization & administration* / Q000592:standards; D013222:State Medicine; D016526:Workload
keywords: Acute; Healthcare data; Modelling; Nurse; Nursing outcomes; Patient safety; Safety; Staffing