Abstract

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 support workers) 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 and their relationship to quality.

Design: Mixed-method (QUAL|QUANT) parallel design with 5 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.

Findings: We will present a logic model of the relationship between staffing and quality.

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 for to make it feasible. Consequently, the effects of the pandemic are reflected in our research methods and findings.

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, high quality training, reinforced by behavioural and relational role modelling by leaders can make the difference when sufficient amounts of consistent staff are employed. More staff alone are unlikely to cost-effectively enhance quality. Social network analysis can help identify the right people to aid adoption and spread of quality and innovation.

Future work: 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.

Slides