Nurse staffing levels and outcomes - mining the UK national datasets for insight.
Leary, A, Tomai, B, Swift, A, Woodward, A and Hurst, K (2017). Nurse staffing levels and outcomes - mining the UK national datasets for insight. International Journal of Health Care Quality Assurance. 30 (3), pp. 235-247.
|Authors||Leary, A, Tomai, B, Swift, A, Woodward, A and Hurst, K|
Purpose - Despite generating mass nursing workforce data, determining the data’s contribution to patient safety remains challenging. Several cross sectional studies indicate a relationship between staffing and safety; our aim, therefore, was to uncover associations and explore if understanding the relationships between staffing and other factors such as safety could be revealed within nationally routinely collected datasets. Design/methodology/approach - Two longitudinal, routinely collected datasets, which include thirty years of UK patient and nursing data, and eleven years of National Health Service benchmark data, such as survey results, safety and other indicators were analysed. A correlation matrix was built and a linear correlation operation was applied using the Pearson product moment correlation coefficient. Findings – Several associations were revealed within the UK nursing and the NHS benchmarking dataset. However, the limitations of using these datasets soon became apparent. Practical implications - Staff time and effort are required to collect these data. Their limitations include inconsistent collection and fidelity/quality of the dataset . The data collection mode and items collected should be reviewed to generate a dataset with robust clinical application. Originality/value - This study revealed that relationships among healthcare variables are likely complex and non-linear. However, the article’s main contribution is identifying routinely collected data’s limitations. Much time and effort is expended collecting healthcare data; however, their usefulness as routinely national data collection require re-examination.
|Journal||International Journal of Health Care Quality Assurance|
|Journal citation||30 (3), pp. 235-247|
|Digital Object Identifier (DOI)||doi:https://doi.org/10.1108/IJHCQA-08-2016-0118|
|01 Jan 2017|
|Publication process dates|
|Deposited||03 Jul 2017|
|Accepted||12 Sep 2016|
|Accepted author manuscript|
CC BY 4.0
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