Estimating length of stay in publicly-funded residential and nursing care homes: a retrospective analysis using linked administrative data sets

• Main Authors: Steventon Adam, Roberts Adam
• Format: Article
• Language: English
• Published: BMC 2012-10-01
• Series: BMC Health Services Research
• Subjects: Care home; Length of stay; Administrative data; Long-term care
• Online Access: http://www.biomedcentral.com/1472-6963/12/377

<p>Abstract</p> <p>Background</p> <p>Information about how long people stay in care homes is needed to plan services, as length of stay is a determinant of future demand for care. As length of stay is proportional to cost, estimates are also needed to inform analysis of the long-term cost effectiveness of interventions aimed at preventing admissions to care homes. But estimates are rarely available due to the cost of repeatedly surveying individuals.</p> <p>Methods</p> <p>We used administrative data from three local authorities in England to estimate the length of publicly-funded care homes stays beginning in 2005 and 2006. Stays were classified into nursing home, permanent residential and temporary residential. We aggregated successive placements in different care home providers and, by linking to health data, across periods in hospital.</p> <p>Results</p> <p>The largest group of stays (38.9%) were those intended to be temporary, such as for rehabilitation, and typically lasted 4 weeks. For people admitted to permanent residential care, median length of stay was 17.9 months. Women stayed longer than men, while stays were shorter if preceded by other forms of social care. There was significant variation in length of stay between the three local authorities. The typical person admitted to a permanent residential care home will cost a local authority over £38,000, less payments due from individuals under the means test.</p> <p>Conclusions</p> <p>These figures are not apparent from existing data sets. The large cost of care home placements suggests significant scope for preventive approaches. The administrative data revealed complexity in patterns of service use, which should be further explored as it may challenge the assumptions that are often made.</p>