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Health Econ. 2005 May;14(5):471-85.

Assessing generalisability by location in trial-based cost-effectiveness analysis: the use of multilevel models.

Author information

1
Centre for Health Economics, University of York, UK. am126@york.ac.uk

Erratum in

  • Health Econ. 2005 May;14(5):486.

Abstract

Cost-effectiveness analysis (CEA) in health care is increasingly conducted alongside multicentre and multinational randomised controlled clinical trials (RCTs). The increased use of stochastic CEA is designed to account for between-patient sampling variability in cost-effectiveness data assuming that observations are independently distributed. However, between-location variability in cost-effectiveness may result if there is a hierarchical structure in the data; that is, if there is correlation in costs and outcomes between patients recruited in particular locations. This may be expected in multi-location trials given that centres and countries often differ in factors such as clinical practice, patient case-mix and the unit costs of delivering health care. A failure to acknowledge this feature may lead to misleading conclusions in a trial-based economic study. Multilevel modelling (MLM) is an analytical framework that can be used to handle hierarchical cost-effectiveness data. Using data from a recently conducted economic analysis, this paper shows how multilevel modelling can be used to obtain (a) more appropriate estimates of the population average incremental cost-effectiveness and associated standard errors compared to standard stochastic CEA; and (b) location-specific estimates of incremental cost-effectiveness which can be used to explore appropriately the variability between centres/countries of the cost-effectiveness results.

PMID:
15386662
DOI:
10.1002/hec.914
[Indexed for MEDLINE]

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