Abstract

Objectives: Little is known about the marginal cost-effectiveness of community-based long-term care (LTC) – or ‘social care’ as it generally known in the UK – especially where effectiveness is rated on ‘utility’ scales. Such information, however, is highly relevant to decision-making about commissioning and resource allocation.

The main aim of this paper was to estimate incremental cost-effectiveness using non-experimental methods and survey data. In particular, the paper sought to estimate the improvement in care-related quality of life (measured in standard utility terms) for an individual that accrues from a small increase in their (cost-weighted) utilisation of community-based LTC. The non-experimental approach was proposed as a practical alternative to experimental evaluation approaches, such as RCTs, which is relevant in this case where services have a self-evident, if non-quantified, effect.

Methods: The paper applied a ‘production function’ method. The basis of this method is that we ought to see a correlation between service utilisation rates and people’s quality of life ratings in a survey of service users, and these relationships can be modelled statistically.

We started with a model that accounts for the mutual dependence in utility as between the cared-for person (patient) and any unpaid carer, based on Becker’s model of altruism in the family. This model formed the basis of our empirical specification. We estimated the relationship between social care-related quality of life (SCRQoL) and LTC-service utilisation rates in a survey of patients and carers. Instrumental variable (IV) estimation was used with control on observable confounders to tackle selection issues. Spatial lags in service use across the sample were the main instruments.

Data: A specifically-designed survey was undertaken which sampled people using publicly-funded long-term care services provided by local authorities in England. Data were collected from 990 service users and from 387 unpaid carers who helped look after a subset of these care recipients.

Results: IV with spatial lags was able to fit reasonable production functions with our survey data. Accordingly, we found that services had statistically-significant marginal effects on care-related quality of life for both cared-for people and unpaid carers. These results were used to calculate incremental cost-effectiveness ratios. We also inferred the strengths and weaknesses of using this approach for evaluation.

Policy implications: An important emergent theme for LTC policy is for funding and commissioning to be guided by information on the relative cost-effectiveness of services and support. The imperative is to make the most effective use of constrained public budgets for care. Moreover, effectiveness is best judged in terms of the impact LTC has on people’s lives, including both service users and carers, and not just on how many services are provided. The methods and results of this paper help to inform these policies.