Decision models as a health intervention assessment tool

Models are approximations, usually mathematical ones, which allow reality to be simulated based on the information of the main events. Their correct design allows information to be obtained about a complex set of events in a context of uncertainty. Pharmaceutical interventions can be analysed by means of models, based on the data obtained in pilot studies, allowing the expected value of the results of interest to be estimated without the need to carry out later studies with a large sample group and/or a longer follow-up.
Health interventions carried out in the heart of processes with defined initial, intermediate and final states of health (such as the case of acute pathologies) can be suitably analysed by means of decision trees. In the case of interventions carried out in processes in which the patient can oscillate between the different states of health, as occurs in chronic pathologies, the handling of the decision trees becomes excessively complex, meaning that the problem is solved by the use of another kind of model, the Markov decision model.
Whatever kind of model is used, the evaluative analysis of the intervention is completed by carrying out various sensitivity analyses, which enable us to estimate the sensitivity of the results in view of the modification of the most relevant variables. This enables us to estimate the expected value of a result in each of the potential scenarios, as well as making a prediction about the threshold values of each variable, based on which, the final result significantly changes its trend. The objective of this chapter is to introduce the community pharmacist to handling the decision models used in the evaluation of pharmaceutical interventions. To facilitate their understanding, two real examples of the use of decision trees (in a programme of child immunisation against rotavirus) and of Markov models (in an intervention to reduce the hospitalisation of elderly people) are presented. They are just two of the many examples of today’s widespread use of decision models in evaluating health interventions.