Artigo de RevisãoEste artigo está publicado em acesso aberto (Open Access) sob a licença Creative Commons, que permite uso, distribuição e reprodução em qualquer meio, sem restrições, desde que o trabalho seja corretamente citado. Estratégias pedagógicas ativas e contribuições para o ensino de promoção da saúde nas universidades Active pedagogical strategies and contributions to health promotion teaching in universitiesEstrategias pedagógicas activas y contribuciones para la enseñanza de promoción de la salud en las universidades

BackgroundThe potential drug-drug interactions (PDDI) in a multidrug treatment (MDT) regimen must be taken into account when prescribing, as adverse effects (AEs) may occur that might make it necessary to choose an alternative treatment.MDT regimens are usually being prescribed by different doctors. This practice increases the risk of DDI and it is fundamental to acknowledge them and identify at-risk patients early.The AEs resulting from DDI can be reduced or avoided with dose adjustments or changes in the regimen, or even stopping some drugs.DDIs can be classified according to severity as major, moderate and minor. The focus of our study was in the group of potential major drug–drug interactions (PMDDI), which can threaten the patient’s life or result in permanent injury.PurposeTo analyse the PDDI profile of medical prescriptions according to severity and identify the most frequent PMDDI and the drugs involved.Material and methodsRetrospective study of PDDIs (checked on Drug Interactions Checker of drugs.com) on all prescriptions of medical ward patients, who were discharged from February to March 2014, by consulting the patient’s clinical record. Descriptive statistical analysis was performed.The following data were collected: number of prescriptions/patient analysed, patients’ average age, average number of prescribed drugs/prescription, maximum number of major interactions/prescription,% of prescriptions with interactions detected; % of prescriptions with potential major interactions (MI), main drugs involved (MD) and more frequent interactions (MFIs).ResultsAbstract PS-077 Table 1Prescriptions/patient analysed234Average age75.3 ± 15.2 years (132?, 102?)Prescribed drugs/prescription11.5 ± 4.5Major interactions/prescription11% of prescriptions with interactions detected97.50% % of prescriptions with potential major interactions71.4% Main drugs involvedEnoxaparin (10.9%)/Potassium Chloride (9%)More frequent interactionsAcetylsalicylic Acid-Enoxaparin (11.1%)ConclusionThe data analysis revealed a huge number of PDDI. This leads us to the conclusion that the pharmacist intervention in this area will increase safety in medicines administration.In future the development of an intervention plan regarding the most frequent PMDDIs will improve the health care provision.It’s our goal to introduce an automatic notification system for the prescriber at the time of prescription in order to manage these interactions.References and/or acknowledgementsNo conflict of interest.