Manca, A., Rice, N., Sculpher, M.J. and Briggs, A.H. (2004) Assessing generalisability by location in trial-based cost-effectiveness analysis: the use of multilevel models. Health Economics, 14 (5). pp. 471-485. ISSN 1057-9230Full text not available from this repository.
An Erratum has been published for this article in Health Economics 14(5) 2005, 486. 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.
|Institution:||The University of York|
|Academic Units:||The University of York > Centre for Health Economics (York)|
|Depositing User:||York RAE Import|
|Date Deposited:||28 May 2009 09:14|
|Last Modified:||28 May 2009 09:14|
|Publisher:||John Wiley & Sons|