The increasing prevalence of children identified with ASDs is described as a national medical emergency by the 2011 Interagency Autism Coordinating Committee (IACC). The IACC developed a strategic plan to address this emergency that if successfully implemented, could greatly improve the quality of life of children with ASDs and their families. This proposal addresses a long-term objective (5.B) in the IACC strategic plan to evaluate the cost-effectiveness of evidence-based services. Cost-effectiveness analysis associated with services and interventions for children with autism also is a priority in PA-10-159 entitled Research on Autism and Autism Spectrum Disorders (R03). Evidence on the cost-effectiveness of interventions for children with ASDs is lacking. This proposal seeks to provide initial information on cost-effectiveness by building on our prior research. The investigators for this study have developed primary data on quality-adjusted life years (QALYs) for children with ASDs that was linked to clinical data associated with their diagnosis and treatment. We then created a mapping algorithm to predict QALYs based on the clinical data. We believe the resulting algorithms could be used to predict QALYs gained associated with different interventions. The findings could then be included in decision-analytic models to predict cost-effectiveness of alternative interventions. To support this research, the investigators need access to data on clinical outcomes of children following a primary intervention. The National Database for Autism Research (NDAR) supports data sharing across NIH-funded autism research projects including clinical, genomic, and brain imaging studies. To date, approximately 80 research projects have shared data in the NDAR database involving 37,659 affected individuals. There are several research projects in NDAR that involved interventions or treatments for children with ASDs. However, none of the projects collected QALY information for economic evaluation of the interventions. The goal of this study is to predict health utility gains from different interventions using the shared data in NDAR and develop decision- analytic models to evaluate cost-effectiveness. Thus, we propose the following three specific aims to achieve our project goal: 1) Summarize data shared in NDAR on interventions to improve core impairments and other associated symptoms in children with ASDs;2) Calculate QALY gains for children with ASDs from selected interventions using data contained in NDAR;and 3) Develop decision-analytic models to describe potential cost-effectiveness of selected interventions for children with ASDs. The findings from the proposed study could be used by a broad spectrum of decision-makers to conduct economic evaluation and allocate resources to support effective interventions for children with ASDs and their families.
Obtaining information of health status improvement for children with autism spectrum disorders (ASDs) in terms of quality-adjusted life year (QALY) gains associated with treatments or interventions is critical for economic evaluations. Evaluation of interventions and treatments according to the cost per QALY metric can help translate effectiveness evidence into sustained practice. Decision-makers can then use this information in evaluating specific treatments or interventions for children with ASDs.
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| Payakachat, Nalin; Tilford, J Mick; Ungar, Wendy J (2016) National Database for Autism Research (NDAR): Big Data Opportunities for Health Services Research and Health Technology Assessment. Pharmacoeconomics 34:127-38 |
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| Payakachat, Nalin; Ali, Mir M; Tilford, J Mick (2015) Can The EQ-5D Detect Meaningful Change? A Systematic Review. Pharmacoeconomics 33:1137-54 |
| Tilford, J Mick; Payakachat, Nalin (2015) Progress in measuring family spillover effects for economic evaluations. Expert Rev Pharmacoecon Outcomes Res 15:195-8 |
| Payakachat, Nalin; Tilford, J Mick; Kuhlthau, Karen A et al. (2014) Predicting health utilities for children with autism spectrum disorders. Autism Res 7:649-63 |
