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Background Drug interactions increase the risk of treatment failure, intoxication, hospital admissions, consultations and mortality. Computer-assisted prescription systems can help to detect interactions. Objectives To describe the drug–drug interaction (DDI) and drug–disease interaction (DdI) prevalence identified by a computer-assisted prescription system in patients with multimorbidity and polypharmacy. Factors associated with clinically relevant interactions were analysed. Methods Observational, descriptive, cross-sectional study in primary health care centres was undertaken in Spain. The sample included 593 patients aged 65–74 years with multimorbidity and polypharmacy participating in the MULTIPAP Study, recruited from November 2016 to January 2017. Drug interactions were identified by a computer-assisted prescription system. Descriptive, bivariate, and multivariate analyses with logistic regression models and robust estimators were performed. Results Half (50.1% (95% CI 46.1–54.1)) of the patients had at least one relevant DDI and 23.9% (95% CI 18.9–25.6) presented with a DdI. Non-opioid–central nervous system depressant drug combinations and benzodiazepine–opioid drug combinations were the two most common clinically relevant interactions (10.8% and 5.9%, respectively). Factors associated with DDI were the use of more than 10 drugs (OR 11.86; 95% CI 6.92–20.33) and having anxiety/depressive disorder (OR 1.98; 95% CI 1.31–2.98). Protective factors against DDI were hypertension (OR 0.62; 95% CI 0.41–0.94), diabetes (OR 0.57; 95% CI 0.40–0.82), and ischaemic heart disease (OR 0.43; 95% CI 0.25–0.74). Conclusion Drug interactions are prevalent in patients aged 65–74 years with multimorbidity and polypharmacy. The clinically relevant DDI frequency is low. The number of prescriptions taken is the most relevant factor associated with presenting a clinically relevant DDI.

Background: Current epidemiological situation has prompted the consideration of multimorbility (MM) as a prevalent condition, influenced by age, educational level and social support, related to unfavorable social and health determinants. Primary Care (PC) has a key role in its approach but further training of professionals in MM is required. The evidence on the effectiveness of training interventions in MM is still limited. Knowing the experiences, opinions and training needs of professionals is essential to enhance training interventions. Objectives: Identify perceived training needs by PC health professionals (doctors and nurses) in MM and polypharmacy. Methods: Design: Cross-sectional study based on an online survey (anonymous-ad hoc questionnaire). Participants and recruitment: 384 doctors and nurses working in healthcare centers and out-of-hospital emergencies of the Spanish National Health System. Non-probabilistic convenience sampling via email addressed to Health Institutions, and social networks. Data: Demographic characteristics and professional profile data (close-ended and multiple-choice questions) will be collected. Open-ended questions will be used to identify training needs, difficulties and resources about MM; required skills to care patients with MM will be assessed using a 4-item ordinal scale. Analysis: Coding of data prior to analysis. Descriptive statistical analysis, participation and completion rates of the questionnaire and estimation of absolute and relative frequencies and 95% confidence intervals in close-ended questions. Content analysis with inductive methodology in open-ended questions. Ethics: Ethical approval, Online informed consent. Conclusions: The identification of training needs of health professionals who care for patients with MM will be necessary data for developing highly effective training activities.