Abstract
Long‐term care services are provided to help people manage the consequences of impairment, but their impact goes beyond the meeting of basic needs. Accordingly, the main aim was to explore the marginal effectiveness of care when measured in terms of people's overall care‐related quality of life (CRQoL) and assess changes in marginal effect for increasing intensity. The associated aim was to refine and apply an observational method to estimate marginal effectiveness. A “production function” approach was used with survey data, including Adult Social Care Outcomes Toolkit‐measured CRQoL, whereby we statistically modelled the expected relationship between service utilisation rates and CRQoL. This method seeks to limit endogeneity issues by controlling on observables and using instrumental variable. Using a survey of publicly funded long‐term care service users in England, we found that community‐based long‐term care significantly improved people's CRQoL but with diminishing marginal effects and effects differentiated by baseline impairment levels. There are implications for how the care system should respond to changes in global public budgets. For example, where there is unmet need, a system aimed to maximise (unadjusted) CRQoL would put more emphasis on access (more recipients) than intensity of support compared to a system operating on a needs basis.
Highlights
We found the instrument to be well balanced with regard to respondent's characteristics
We did not use logged dependent variable specifications in the main model because the care‐related quality of life (CRQoL) includes negative values and the logged distribution was further away from the normal distribution compared to the linear version—see Figure 2
In line with our first hypothesis, we found a significant positive effect of service utilisation on quality of life (CRQoL)
Summary
The utility of a person (i) with care needs—denoted by Ui—is likely to be affected by the severity of their condition and other needs‐related circumstances (uni ), the use of informal care (Yi), and the amount of care services they utilise. The spatial lag instrument seeks to capture differences in policy and supply between care authorities Because this variable is partly defined at the LA level, there is a possibility that it might be correlated with factors that vary on a geographical basis, where these factors could have a direct effect on CRQoL. The information collected included socio‐demographic characteristics, service receipt (i.e., publicly funded, self‐ funded, and informal), well‐being, health status, functional ability, control and autonomy, suitability of home and local environment for mobility needs, social contact and support, and participation in social groups (Forder et al, 2015) This analysis used an (anonymised) sample including those with physical disability or sensory impairment and mental health. The ASCOT indicators are preference‐weighted quality of life measures anchored around quality of life states equivalent to being dead (a score of 0) and having a score of 1 if a person chooses the highest levels on each attribute
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