Objective. To investigate the status of pharmacoeconomics education in Egyptian schools of pharmacy and compile and construct recommendations on how Egypt and similar countries could improve their educational infrastructure in pharmacoeconomics. Methods. A modified version of a published survey instrument was sent to all schools of pharmacy in Egypt (n5 24). The data were assessed to identify associations between offering pharmacoeconomics education and school characteristics. Results. Usable responses were obtained from 20 schools (response rate: 83%). Only 7 schools offered pharmacoeconomics education, with a median of 20 teaching hours per semester. Among respondents, 4 schools had instructors with some training in pharmacoeconomics and only 1 school had a faculty member with PhD-level training. Only 4 schools offered graduate-level courses in pharmacoeconomics. Eight additional schools expressed interest in teaching pharmacoeconomics in the near future. Having 1 or more faculty members with training in pharmacoeconomics was significantly associated with offering pharmacoeconomics education (p 5 0.03). Conclusions. Pharmacoeconomics education in Egypt is still in its infancy and there exists a unique opportunity for well-trained instructors and researchers to fill this gap. Providing structured pharmacoeconomics education to student pharmacists, researchers, and stakeholders can help countries establish an integrated scientific community that can start applying pharmacoeconomic evidence to healthcare decision-making.
2+, 3+. States: A feature selection is executed by a modeler who decides which set of features describes a disease state or patient cohort best. For identifying the most relevant attribute combinations a cluster analysis is applied beforehand. Transitions: Patients remain in one particular state as long as they match the predetermined features and attributes. Otherwise, a change to another state occurs. Thereby, a sequence of states for each patient is defined. As a final step, these sequences are used for deriving a model structure. ExpEctEd REsults: Markov models backed up by real-life patient records. As a result of the automatic generation process models can be used for validating hypotheses or comparing outcomes for different patient cohorts. Therefore, the usage of such models is not strictly limited to health economic analysis. A first validation indicates the feasibility of the outlined methods. It was possible to reconstruct a published disease model. conclusions: Ongoing research is conducted with focus on data quality, i.e., accuracy, completeness and timeliness, at the regional cancer registry.
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