Cost-Effectiveness Evaluation for Services Provided to People with Autism: Update and Recommendations

Background:  Cost-effectiveness analysis is a tool that can be useful for autism research and policy. For example, findings from a cost-effectiveness analysis can be used to identify clinical comparative effectiveness research that should be rapidly translated into practice. It can also inform policy about coverage for services and optimal treatment strategies. Unfortunately, there is a lack of understanding about the role and practice of cost-effectiveness that impedes its use among practitioners.

Objectives:  The purpose of this paper is to describe state of the art approaches for evaluating the cost-effectiveness of services provided to people with autism specifically focusing on children.

Methods:  The US Panel on Cost-Effectiveness in Health and Medicine developed guidelines for conducting cost-effectiveness analysis to create a standard approach so that findings could be compared across different studies, conditions, and population groups. Guidelines exist for other countries, especially the UK, but they differ on specific issues. This paper reviews guidelines for measuring quality adjusted life years and costs to conduct a cost-effectiveness analysis from a societal perspective. We note the special features of child health services that pertain to children with autism. In particular, children with autism are more likely to receive services in multiple settings that create difficulties in measuring costs, there are issues in measuring quality adjusted life years (QALYs) particularly in young children, and family spillover effects can play an important role in calculating the benefits of the intervention. We illustrate these issues using specific examples based on recent findings.

Results:  Only one cost-effectiveness evaluation has been conducted on services for people with autism that followed either the US or UK guidelines. In that study, supported employment was found to produce a cost-effectiveness ratio of £5600 per QALY suggesting that such a practice should be adopted on a larger scale. The study lacked data on health utilities for calculating QALYs and had to extrapolate estimates from other conditions. There are no cost-effectiveness evaluations for services provided to children with autism using the cost per QALY metric, despite significant advances in utility data for measuring QALYs. Finally, there is evidence that services for children with autism produce spillover utility benefits for family members and failure to include these benefits can lead to cost-effectiveness ratios that understate the true value of the services provided.

Conclusions:  Practitioners in the field of autism research can benefit from a greater understanding of cost-effectiveness evaluation to prioritize service delivery and influence policy. There are a number of exciting developments in the field of cost-effectiveness evaluation relevant to autism research, especially the measurement of QALYs in children and spillover effects of services on family outcomes.