data envelopment analysis ( dea ) is a useful tool to evaluate technical efficiency when a range of comparable decision making units ( dmu ) are involved in an uncertain system . dea models , based on expert knowledge , must be carefully fitted to represent the framework under study . the model has been applied to the assessment of technical efficiency of small mental health areas ( smha ) , composed by a complex array of social and health services . the dmus input / output algebraic behaviour was adjusted to an expert - driven model of community care ( b - mhcc ) . a preliminary version of the model has been applied to the assessment of divergent smha in spain and in chile . the probability of being efficient of 71 smha were analysed in andalusia ( spain ) using large health databases . the model has shown its usability to identify both efficiency and inefficiency under uncertainty of highly complex dmus . for all non - efficient sha , i / o improvements needed to reach efficiency were also evaluated . expert - driven monte - carlo dea is a powerful tool to evaluate relative technical efficiency . algebraic models need to be carefully fitted by expert knowledge and information transfer strategies should be included in model development . due to the system complexity , there are many sha that can be considered efficient and many i / o profiles can be used for benchmarking .
introductioninformation transfer is critical in evaluating the efficiency of health and social care systems . 
 data envelopment analysis ( dea ) is a useful tool to evaluate technical efficiency when a range of comparable decision making units ( dmu ) are involved in an uncertain system . 
 dea models , based on expert knowledge , must be carefully fitted to represent the framework under study.theory and methodswe designed a monte - carlo dea model based on adjusted expert knowledge . 
 the model has been applied to the assessment of technical efficiency of small mental health areas ( smha ) , composed by a complex array of social and health services . 
 the dmus input / output algebraic behaviour was adjusted to an expert - driven model of community care ( b - mhcc ) . 
 a preliminary version of the model has been applied to the assessment of divergent smha in spain and in chile . 
 the probability of being efficient of 71 smha were analysed in andalusia ( spain ) using large health databases.resultsthe model has shown its usability to identify both efficiency and inefficiency under uncertainty of highly complex dmus . 
 for all non - efficient sha , i / o improvements needed to reach efficiency were also evaluated . 
 results show significant differences between sha in andalusia.conclusionsexpert-driven monte - carlo dea is a powerful tool to evaluate relative technical efficiency . 
 algebraic models need to be carefully fitted by expert knowledge and information transfer strategies should be included in model development.discussiondue to the system complexity , there are many sha that can be considered efficient and many i / o profiles can be used for benchmarking .