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.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. DISCUSSION: 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. CONCLUSION: 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 design and (human) resource allocation. Further experimental research is required to elucidate resource-specific thresholds and further strengthen evidence for care home staffing. TWEETABLE ABSTRACT: How much nursing care is needed to assure quality in care homes? Evidence from 2 English care home providers shows that nurse sensitive outcomes (an indicator of quality) are better when ~25 % of care is provided by nurses. Nurse shortages increase risks for residents.

Relationship between staff and quality of care in care homes: StaRQ mixed methods study.

Background: Quality of life and care varies between and within the care homes in which almost half a million older people live and over half a million direct care staff (registered nurses and care assistants) work. The reasons are complex, understudied and sometimes oversimplified, but staff and their work are a significant influence. Objective(s): To explore variations in the care home nursing and support workforce; how resident and relatives' needs in care homes are linked to care home staffing; how different staffing models impact on care quality, outcomes and costs; how workforce numbers, skill mix and stability meet residents' needs; the contributions of the care home workforce to enhancing quality of care; staff relationships as a platform for implementation by providers. Design: Mixed-method (QUAL-QUANT) parallel design with five work packages. WP1 - two evidence syntheses (one realist); WP2 - cross-sectional survey of routine staffing and rated quality from care home regulator; WP3 - analysis of longitudinal data from a corporate provider of staffing characteristics and quality indicators, including safety; WP4 - secondary analysis of care home regulator reports; WP5 - social network analysis of networks likely to influence quality innovation. We expressed our synthesised findings as a logic model. Setting: English care homes, with and without nursing, with various ownership structures, size and location, with varying quality ratings. Participants: Managers, residents, families and care home staff. Findings: Staffing's contribution to quality and personalised care requires: managerial and staff stability and consistency; sufficient staff to develop 'familial' relationships between staff and residents, and staff-staff reciprocity, 'knowing' residents, and skills and competence training beyond induction; supported, well-led staff seeing modelled behaviours from supervisors; autonomy to act. Outcome measures that capture the relationship between staffing and quality include: the extent to which resident needs and preferences are met and culturally appropriate; resident and family satisfaction; extent of residents living with purpose; safe care (including clinical outcomes); staff well-being and job satisfaction were important, but underacknowledged. Limitations: Many of our findings stem from self-reported and routine data with known biases - such as under reporting of adverse incidents; our analysis may reflect these biases. COVID-19 required adapting our original protocol to make it feasible. Consequently, the effects of the pandemic are reflected in our research methods and findings. Our findings are based on data from a single care home operator and so may not be generalised to the wider population of care homes. Conclusions: Innovative and multiple methods and theory can successfully highlight the nuanced relationship between staffing and quality in care homes. Modifiable characteristics such as visible philosophies of care and high-quality training, reinforced by behavioural and relational role modelling by leaders can make the difference when sufficient amounts of consistent staff are employed. Greater staffing capacity alone is unlikely to enhance quality in a cost-effective manner. Social network analysis can help identify the right people to aid adoption and spread of quality and innovation. Future research should focus on richer, iterative, evaluative testing and development of our logic model using theoretically and empirically defensible - rather than available - inputs and outcomes. Study registration: This study is registered as PROSPERO CRD42021241066 and Research Registry registration: 1062. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 15/144/29) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 8. See the NIHR Funding and Awards website for further award information.

This study was about the relationship between staffing and quality in care homes. Almost half a million older people live in care homes in England. Why quality of care and quality of life for residents vary so much between and within homes is unknown, but staff and the ways they work are likely to be important. Researching staffing and quality is difficult: quality means different things to different people and a lot of things shape how quality feels to residents, families and staff. In the past, researchers have oversimplified the problem to study it and may have missed important influences. We took a more complex view. In five interlinked work packages, we collected and analysed: (1) research journal articles; (2) national data from different care homes; (3) data from a large care organisation to look at what it is about staffing that influences quality; (4) reports and ratings of homes from the Care Quality Commission; and (5) we looked at the networks between staff in homes that shape how quality improvement techniques might spread. We used theories about how our findings might be linked to plan for this data collection and analysis. The results were combined into something called a 'logic model' ­ a diagram and explanation that make it easier for managers, researchers and people interested in care homes to see how staffing influences quality. Staffing considerations that might improve quality include: not swapping managers too much; having sufficient and consistent staff for family-like relationships in homes and putting residents' needs first; supporting staff and giving them freedom to act; and key staff leading by example. Research examining care home quality should capture those aspects that mean the most to residents, their families and staff.

Inequalities in the disruption of paid work during the Covid-19 pandemic: A world systems analysis of core, semi-periphery, and periphery states.

This article reveals the extent of international inequalities in the immediate impact of the COVID-19 pandemic on participation in paid work. Drawing on World Systems Theory (WST) and a novel quasi-experimental analysis of nationally representative household panel surveys across 20 countries, the study finds a much sharper increase in the likelihood of dropping out of paid work in semi-periphery and periphery states relative to core states. We establish a causal link between such international disparities and the early trajectories of state interventions in the labor market. Further analysis demonstrates that within all three world systems delayed, less stringent interventions in the labor market were enabled by right-wing populism but mitigated by the strength of active labor market policies and collective bargaining.

Understanding the staff behaviours that promote quality for older people living in long term care facilities: A realist review.

BACKGROUND: Little is known about how the workforce influences quality in long term care facilities for older people. Staff numbers are important but do not fully explain this relationship. OBJECTIVES: To develop theoretical explanations for the relationship between long-term care facility staffing and quality of care as experienced by residents. DESIGN: A realist evidence synthesis to understand staff behaviours that promote quality of care for older people living in long-term care facilities. SETTING: Long-term residential care facilities PARTICIPANTS: Long-term care facility staff, residents, and relatives METHODS: The realist review, (i) was co-developed with stakeholders to determine initial programme theories, (ii) systematically searched the evidence to test and develop theoretical propositions, and (iii) validated and refined emergent theory with stakeholder groups. RESULTS: 66 research papers were included in the review. Three key findings explain the relationship between staffing and quality: (i) quality is influenced by staff behaviours; (ii) behaviours are contingent on relationships nurtured by long-term care facility environment and culture; and (iii) leadership has an important influence on how organisational resources (sufficient staff effectively deployed, with the knowledge, expertise and skills required to meet residents' needs) are used to generate and sustain quality-promoting relationships. Six theoretical propositions explain these findings. CONCLUSION: Leaders (at all levels) through their role-modelling behaviours can use organisational resources to endorse and encourage relationships (at all levels) between staff, residents, co-workers and family (relationship centred care) that constitute learning opportunities for staff, and encourage quality as experienced by residents and families.

Privileges and penalties in the legal profession: an intersectional analysis of career progression.

Intersectionality theory is concerned with integrating social characteristics to better understanding complex human relations and inequalities in organizations and societies (McCall 2005). Recently, intersectionality research has taken a categorical and quantitative turn as scholars critically adopt but retain existing social categories to explain differences in labour market outcomes. A key contention is that social categories carry penalties or privileges and their intersection promotes or hinders the life chances of particular groups and individuals. An emergent debate is whether the intersection of disadvantaged characteristics (such as female gender or minority ethnic status) produce penalties that are additive, multiplicative or ameliorative. Research is inconclusive and as yet pays little attention to moderating factors such as employer type, size, geographic location or work profile. Drawing on administrative records for individuals qualified as solicitors in England and Wales, collected by the Solicitors Regulation Authority (SRA), combined with aggregated workforce data and firm characteristics of their law firms, we undertake a statistical analysis of the intersection of gender and ethnicity in the profession with a degree of precision and nuance not previously possible. In response to calls to broaden studies of inequalities and intersectionality beyond their effect on pay or income (Castilla 2008) we focus on career progression to partnership as our key measure of success. The original contribution of our study is twofold. First, we establish statistically different profiles of law firms, showing how the solicitors' profession is stratified by gender, ethnicity and socio-economic background, as well as the type of legal work undertaken by developing a model of socio-economic stratification in the profession. Second, we demonstrate that while penalties tend to be additive (i.e. the sum of the individual ethnic and gender penalties) this varies significantly by law firm profile and in some situations the effect is ameliorative.