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Relationship between staff and quality of care in care homes: StaRQ mixed methods study
Apr 18, 2024Health and social care delivery research
How staff relationships relate to quality of care in care homes
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Abstract
Staffing levels and their characteristics are associated with the quality of care in English care homes.
- Managerial and staff stability is important for delivering quality and personalized care.
- Sufficient staffing fosters familial relationships between staff and residents, enhancing care quality.
- The skills and competence training of staff needs to extend beyond initial induction to improve outcomes.
- The relationship between staffing and care quality includes resident satisfaction, safety, and well-being.
- Underreported biases in self-reported and routine data may affect findings and conclusions.
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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; Vol. 12, No. 8. See the NIHR Funding and Awards website for further award information. Health and Social Care Delivery Research
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