Workforce thresholds and the non-linear association between registered nurse staffing and care quality in long-term residential care: A retrospective longitudinal study of English care homes with nursing

Care needs amongst 425,000 dependent older residents in English care homes are becoming more complex. The quality of care in these homes is influenced by staffing levels, especially the presence of registered nurses (RNs). Existing research on this topic, often US-focused and relying on linear assumptions, has limitations. This study aims to investigate the non-linear relationship between RN staffing and care quality in English care homes using machine learning and administrative data from two major care home providers. A retrospective observational study was conducted using data from two English care home providers. Each was analysed separately due to variations in data reporting and care processes. Various care quality indicators and staffing metrics were collected for a 3.5-year period. Regression analysis and machine learning (random forest) were employed to identify non-linear relationships. Ethical approval was obtained for the study. Using linear methods, higher skill mix – more care provided by RNs – was associated with lower incidence of adverse outcomes, such as urinary tract infections and hospitalisations. However, non-linear skill mix–outcome relationship modelling revealed both low and high skill mix levels were linked to higher risks. The effects of agency RN usage varied between providers, increasing risks in one but not the other. The study highlights the cost implications of increasing RN staffing establishments to improve care quality, suggesting a non-linear relationship and an optimal staffing threshold of around one-quarter of care provided by nurses. Alternative roles, such as care practitioners, merit exploration for meeting care demands whilst maintaining quality. This research underscores the need for a workforce plan for social care in England. It advocates for the incorporation of machine learning models alongside traditional regression-based methods. Our results may have limited generalisability to smaller providers and experimental research to redesign care processes effectively may be needed. RNs are crucial for quality in care homes. Contrary to the assumption that higher nurse staffing necessarily leads to better care quality, this study reveals a nuanced, non-linear relationship between RN staffing and care quality in English care homes. It suggests that identifying an optimal staffing threshold, beyond which increasing nursing inputs may not significantly enhance care quality may necessitate reconsidering care system desi