Long-term care and hospital utilisation by older people: an analysis of substitution rates
Health Economics 18 11 1322-1338
Available online: 10 February 2009
Abstract
Older people are intensive users of hospital and long-term care services. This paper explores the extent to which these services are substitutes. A small area analysis was used with both care home and (tariff cost-weighted) hospital utilisation for older people aggregated to electoral wards in England. Health and social-care structural equations were specified using a theoretical model. The estimation accounted for the skewed and censored nature of the data. For health utilisation, both a fixed effects instrumental variables GMM model and a generalised estimating equations (GEE) model were fitted, the later on a log dependent variable with predicted values of social care utilisation used to account for endogeneity (bootstrapping was used to derive standard errors). In addition to a GMM model, the social-care estimation used both two-part and tobit models (also with predicted health utilisation and bootstrapping). The results indicate that for each additional £1 spent on care homes, hospital expenditure falls by £0.35. Also, £1 additional hospital spend corresponds to just over £0.35 reduction on care home spend. With these cost substitution effects offsetting, a transfer of resources to care homes is efficient if the resultant outcome gain is greater than the outcome loss from reduced hospital use
Older people are intensive users of hospital and long-term care services. This paper explores the extent to which these services are substitutes. A small area analysis was used with both care home and (tariff cost-weighted) hospital utilisation for older people aggregated to electoral wards in England. Health and social-care structural equations were specified using a theoretical model. The estimation accounted for the skewed and censored nature of the data. For health utilisation, both a fixed effects instrumental variables GMM model and a generalised estimating equations (GEE) model were fitted, the later on a log dependent variable with predicted values of social care utilisation used to account for endogeneity (bootstrapping was used to derive standard errors). In addition to a GMM model, the social-care estimation used both two-part and tobit models (also with predicted health utilisation and bootstrapping). The results indicate that for each additional £1 spent on care homes, hospital expenditure falls by £0.35. Also, £1 additional hospital spend corresponds to just over £0.35 reduction on care home spend. With these cost substitution effects offsetting, a transfer of resources to care homes is efficient if the resultant outcome gain is greater than the outcome loss from reduced hospital use