Medication regimen complexity in institutionalized elderly people in an aging society

Background Complex medication regimens may adversely affect compliance and treatment outcomes. Complexity can be assessed with the medication regimen complexity index (MRCI), which has proved to be a valid, reliable tool, with potential uses in both practice and research. Objective To use the MRCI to assess medication regimen complexity in institutionalized elderly people. Setting Five nursing homes in mainland Portugal. Methods A descriptive, cross-sectional study of institutionalized elderly people (n = 415) was performed from March to June 2009, including all inpatients aged 65 and over taking at least one medication per day. Main outcome measure Medication regimen complexity index. Results The mean age of the sample was 83.9 years (±6.6 years), and 60.2 % were women. The elderly patients were taking a large number of drugs, with 76.6 % taking more than five medications per day. The average medication regimen complexity was 18.2 (±SD = 9.6), and was higher in the females (p < 0.001). The most decisive factors contributing to the complexity were the number of drugs and dosage frequency. In regimens with the same number of medications, schedule was the most relevant factor in the final score (r = 0.922), followed by pharmaceutical forms (r = 0.768) and additional instructions (r = 0.742). Conclusion Medication regimen complexity proved to be high. There is certainly potential for the pharmacist’s intervention to reduce it as part as the medication review routine in all the patients.

Logic Programming and Artificial Neural Networks in Pharmacological Screening of Schinus Essential Oils

Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.