Advancing quantitative methods for the evaluation of complex interventions
journal contributionposted on 02.08.2016, 15:21 by Clare Gillies, N. Freemantle, R. Grieve, J. Sekhon, J. Forder
An understanding of the impact of health and care interventions and policy is essential for decisions about which to fund. In this essay we discuss quantitative approaches in providing evaluative evidence. Experimental approaches allow the use of ‘gold-standard’ methods such as randomised controlled trials to produce results with high internal validity. However, the findings may be limited with regard to generalisation: that is, feature reduced externality validity. Observational quantitative approaches, including matching, synthetic control and instrumental variables, use administrative, survey and other forms of ‘observational’ data, and produce results with good generalisability. These methods have been developing in the literature and are better able to address core challenges such as selection bias, and so improve internal validity. Evaluators have a range of quantitative methods available, both experimental and observational. It is perhaps a combination of these approaches that is most suited to evaluating complex interventions.