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

Spilsbury K, Charlwood A, Thompson C, Haunch K, Valizade D, Devi R, Jackson C, Alldred DP, Arthur A, Brown L, Edwards P, Fenton W, Gage H, Glover M, Hanratty B, Meyer J, Waton A
Record ID 32018012046
Authors' objectives: 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. 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. An estimated 425,000 older people in England live in 18,000 care homes: with nursing, without nursing, or dual registered homes. They are some of the oldest and the most vulnerable people in society. Resident dependency levels and care needs are often similar in homes with and without nursing – but their workforces differ significantly. In homes with nursing care, registered nurses (RNs) are employed to provide clinical care and supervise care delivery, mainly from a large workforce of non-registered care assistants. Care homes without nursing comprise only social care staff or care assistants. The NHS provides health care – including nursing care – as required; for example, supporting specialist care for residents at the end of life. Staffing profiles and establishments vary between providers and so studying care homes and their workforce is complex. Conceptually, quality is similarly complex; it is contested, contingent, contextualised, dynamic and often deeply personal. Two dimensions of quality require consideration in care homes: quality of care and quality of life. While care home staff and their work are likely determinants of quality, research into the staffing–quality relationship is comparatively scant. Measuring quality often focuses on clinical outcomes, such as pressure ulcer prevalence, falls or medication errors. Many studies are in North American long-term care and the few English studies’ primary focus has been on staff turnover and quality and working conditions and quality. Our mixed-methods study addresses some of the theoretical gaps and methodological challenges associated with understanding staffing’s relationship to quality. Using established theory we focused on the structures, processes and outcomes of quality. Our aim of investigating workforce models of nursing and care support in care homes that effectively benefit residents, relatives and staff was addressed through six objectives, which were the focus of five linked work packages (WP). Describe variations in the characteristics of the care home nursing and support workforce (WP1). Identify the dependency and needs of residents and relatives in care homes and their association with care home staffing (WP2, WP3). Examine how different care home staffing models (including new roles) impact on quality of care, resident outcomes and NHS resources (WP1, WP2, WP3). Explain how care home workforce (numbers, skill mix and stability) might meet the dependency and needs of residents (WP1, WP2, WP3, WP4). Explore and understand the contributions of the nursing and support workforce (including innovations in nursing and support roles) in care homes to enhance quality of care (WP1, WP4). Translate methods used for modelling the relationships between staffing and quality to provide a platform for sector-wide implementation (WP5).
Authors' results and 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. Our study makes a novel and important contribution to understanding the importance of the relationship between staff, their work and behaviours and quality in care homes. We have attempted to shift the debate away from a reductionist picture of numbers of staff and their relationship to clinical indicators, towards a more nuanced recognition of the ways in which staff in the right amounts and with the right behaviours can meet resident’s needs and preferences. Staffing needs to be stable, skilled and competent to realise the benefits of person-focused organisation of care, and enhanced teamworking. Leadership, reward and recognition of staff and a shared philosophy of care provide needed context for the relationships required to improve quality as experienced by residents. Our findings will be useful for people and organisations making policy and delivering services that want to work towards the best ways to deploy and support quality in care homes using their most valuable resource: their staff.
Authors' methods: 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. English care homes, with and without nursing, with various ownership structures, size and location, with varying quality ratings. Managers, residents, families and care home staff. 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. A mixed-method (QUAL-QUANT) parallel design built around Donabedian’s theoretical framework of structures, processes and outcomes was the basis for our exploration of the relationship between care home staffing and quality. The coronavirus disease 2019 (COVID-19) pandemic meant some deviation from our original protocol was necessary. Work package 1 (WP1) was two evidence reviews: a systematic review synthesising 36 studies of care home staff perceptions of their roles and responsibilities in promoting quality; a realist review (n = 66 studies) then developed evidence and theory-based explanations of how care home staff behaviours promote quality of care and quality of life, why and in what circumstances. Work packages 2 and 3 used routinely collected measures of staffing and examined their relationship to quality. WP2 was a cross-sectional observational study, modelling the relationship between care quality – as measured in Care Quality Commission (CQC) inspection reports – and care home workforce characteristics from the National Minimum Data Set for Social Care (NMDS-SC). WP3 analysed routinely collected longitudinal data measures of workforce, nurse-sensitive indicators of care quality, resident characteristics and home characteristics from a large corporate care home provider over 42 months. A cost analysis from a provider perspective was also undertaken. Work package 4 used documentary analysis of 30 purposively sampled, publicly available, inspection reports from the English national quality regulator (CQC) from homes rated as outstanding or inadequate to examine (1) how staffing structures influenced quality and (2) the care processes that explain the relationship between staffing and quality. In WP5, care homes (n = 11) were purposively sampled and social network analysis (SNA) using questionnaires and roster name generation was used to map the self-reported advice and influence relationships present in care homes. To assess homes’ readiness for innovation and work-related barriers to adoption of our (translated) findings, eight managers completed an adapted version of the Normalisation MeAsure Development questionnaire (NoMAD) questionnaire – an operationalised instrument of Normalisation Process Theory.
Project Status: Completed
Year Published: 2024
URL for additional information: English
English language abstract: An English language summary is available
Publication Type: Full HTA
Country: United Kingdom
MeSH Terms
  • Nursing Homes
  • Quality of Health Care
  • Quality of Life
  • Long-Term Care
  • Aged
  • Homes for the Aged
  • Personnel Staffing and Scheduling
  • Nurses
Organisation Name: NIHR Health and Social Care Delivery Program
Contact Name: Rhiannon Miller
Contact Email:
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