Overall , the cohort Markov models remain the most popular approach , followed by decision trees , Individual based model and System dynamics model ( SD ) .
Conclusions This review paper informs policy makers about the availability of modelling techniques that can be used to enhance the quality of economic evaluations for drug and alcohol treatment interventions
Background The overarching goal of health policies is to maximize health and societal benefits .
Economic evaluations can play a vital role in assessing whether or not such benefits occur .
This paper review s the application of modelling techniques in economic evaluations of drug and alcohol interventions with regard to ( i ) modelling paradigms themselves ; ( ii ) perspectives of costs and benefits and ( iii ) time frame .
The cost-effectiveness and public health benefit of nalmefene added to psychosocial support for the reduction of alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels: a Markov model
Objectives To determine whether nalmefene combined with psychosocial support is cost-effective compared with psychosocial support alone for reducing alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels ( DRLs ) as defined by the WHO , and to evaluate the public health benefit of reducing harmful alcohol-attributable diseases , injuries and deaths . Design Decision modelling using Markov chains compared costs and effects over 5 years . Setting The analysis was from the perspective of the National Health Service ( NHS ) in Engl and and Wales . Participants The model considered the licensed population for nalmefene , specifically adults with both alcohol dependence and high/very high DRLs , who do not require immediate detoxification and who continue to have high/very high DRLs after initial assessment . Data sources We modelled treatment effect using data from three clinical trials for nalmefene ( ESENSE 1 ( NCT00811720 ) , ESENSE 2 ( NCT00812461 ) and SENSE ( NCT00811941 ) ) . Baseline characteristics of the model population , treatment re source utilisation and utilities were from these trials . We estimated the number of alcohol-attributable events occurring at different levels of alcohol consumption based on published epidemiological risk-relation studies . Health-related costs were from UK sources . Main outcome measures We measured incremental cost per quality -adjusted life year ( QALY ) gained and number of alcohol-attributable harmful events avoided .  Results Nalmefene in combination with psychosocial support had an incremental cost-effectiveness ratio ( ICER ) of £ 5204 per QALY gained , and was therefore cost-effective at the £ 20 000 per QALY gained decision threshold . Sensitivity analyses showed that the conclusion was robust . Nalmefene plus psychosocial support led to the avoidance of 7179 alcohol-attributable diseases/injuries and 309 deaths per 100 000 patients compared to psychosocial support alone over the course of 5 years . Conclusions Nalmefene can be seen as a cost-effective treatment for alcohol dependence , with substantial public health benefits . Trial registration numbers This cost-effectiveness analysis was developed based on data from three r and omised clinical trials : ESENSE 1 ( NCT00811720 ) , ESENSE 2 ( NCT00812461 ) and SENSE ( NCT00811941 )
Overall , the cohort Markov models remain the most popular approach , followed by decision trees , Individual based model and System dynamics model ( SD ) .
Conclusions This review paper informs policy makers about the availability of modelling techniques that can be used to enhance the quality of economic evaluations for drug and alcohol treatment interventions
Background The overarching goal of health policies is to maximize health and societal benefits .
Economic evaluations can play a vital role in assessing whether or not such benefits occur .
This paper review s the application of modelling techniques in economic evaluations of drug and alcohol interventions with regard to ( i ) modelling paradigms themselves ; ( ii ) perspectives of costs and benefits and ( iii ) time frame .