Title: Building a policy and sector-relevant evidence-base of the relationships between care home staffing and quality: developing insights and using novel methodological approaches
Funder: Department of Health and Social Care

Abstract: Staffing is the largest operating cost in care homes and drives quality of care. In recent years, quality of care in the sector has come under increasing scrutiny, and concerns raised about the levels, recruitment and retention of staff, as well as quality. Beyond broad recognition that staff influence quality , little is known about the UK care home workforce s relationship to quality of care. Our study aims to develop policy and sector-relevant research exploring, testing and predicting the relationships between workforce, quality, outcomes and costs in care homes. The study builds on our ongoing research programme (funded by NIHR HSDR) by enabling us to collaborate with HC-One, the largest UK provider of care homes, and access their unique data on workforce and resident health outcomes. Four objectives help address our aim and include to: examine relationships with periods of below-protocol staffing and nurse-sensitive indicators of care; test whether the stability and experience of the nursing and care workforce in care homes is associated with better quality (measured using nursing-sensitive indicators of care); assess the costs to care homes, and the NHS, of below-target and unstable staffing in care homes; and translate the findings into usable recommendations for policy makers and provide a platform for sector-wide learning. Our methodological approach is informed by a critical appreciation of existing and ongoing research, and well established theories of quality. The work has two sequential stages: first, longitudinal modelling of relationships between staffing inputs (including direct care and nursing hours), quality outcomes (such as pressure ulcers and unplanned hospital admissions) and costs using routine data collected by HC-One (objectives 1 to 3). We will calculate the incremental staffing requirements necessary for care homes to improve quality, and the costs associated with achieving better quality and outcomes. Second, we will engage stakeholders (including families, regulators, commissioners and policy makers) in six regional discussions to both share our results and better explain and contextualise the results (objective 4); helping us translate results into recommendations for effective spread and uptake to enhance care quality by the care home sector. Our team of experienced academic researchers, care home provider and user experience representatives means we can successfully deliver and complete this project. The Study Steering Committee for our current research programme will oversee and shape our work, alongside other advisory groups made up of (i) residents and relatives, (ii) care home managers, and (iii) policy makers. Our theoretically-informed, structured, dissemination strategy, tailored to residents and relatives, policy makers, commissioners, regulators, and care providers, will ensure the findings are accessible. We will use our existing networks as a platform to maximise opportunities for sharing learning from the project and encouraging implementation into practice. We will produce evidence to inform policy and organisational (care home) level decisions about staffing and best ways to deploy the staffing resource within care homes.

Lay abstract: The quality of care that the 420,000 older people living in care homes receive depends a lot on the staff who are looking after them. Currently there is not much evidence about how the number of staff in care homes, and their training levels, affects the care that residents receive in the UK. We are already undertaking a study to look into this important issue. This proposal is for us to extend our existing work.. We now have the opportunity to use information collected by one of the UK s largest care home provider organisations, HC-One. We will use statistical methods to look at the relationship between the staff (such as the mix of staff that work in homes, the hours they work, turnover in the home and how many agency staff homes use) and measures of quality of care (such having to go to hospital unexpectedly or pressure ulcers). We will take into account differences between care homes and residents. This means differences in quality will be because of the numbers and types of workers and the sorts of things they do. HC-One s dataset is very large, so we can try new ways of analysing the data. These new ways of looking at staffing and quality statistically should lead to more informed policies on staffing. We have successfully tested these methods in our current work and we know they are feasible. The financial costs of both good and poor quality matter; we will predict how much money it will take to raise quality through staffing and the impacts on quality of varied spending on staff in the health and social care system. Finally, we will bring together care home owners, families, the Care Quality Commission, Local Authorities and policy makers in six workshops around the country to share our results. This will help us improve how we explain the results and encourage better ways of getting people to use the results for management decisions and policy. As a team, we have worked with care homes for a long time; so we are confident we can deliver and complete this project on time and within its budget. We have a Study Steering Committee that will check our work and also other advisory groups (made up of residents and relatives, care home staff and policy makers) to help shape our ideas. Telling others (care home owners, managers, staff groups, families and policy makers) what we have done and found, and what it means for them, requires using lots of approaches to reach as many people as possible. We will use plain English and our existing networks to share findings and encourage people to use these in their planning and decision making.

Research activity codes: 8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: GENERIC HEALTH RELEVANCE