Objective To estimate the prevalence of nonadherence to treatment and its relationship with social support and social context in patients with multimorbidity and polypharmacy followed-up in primary care. Methods This was an observational, descriptive, cross-sectional, multicenter study with an analytical approach. A total of 593 patients between 65-74 years of age with multimorbidity (�3 diseases) and polypharmacy (�5 drugs) during the last three months and agreed to participate in the MULTIPAP Study. The main variable was adherence (Morisky-Green). The predictors were social support (structural support and functional support (DUFSS)); sociodemographic variables; indicators of urban objective vulnerability; health-related quality of life (EQ-5D-5L-VAS & QALY); and clinical variables. Descriptive, bivariate and multivariate analyses with logistic regression models and robust estimators were performed.

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(1) Purpose: To investigate a complex MULTIPAP intervention that implements the Ariadne principles in a primary care population of young-elderly patients with multimorbidity and polypharmacy and to evaluate its effectiveness for improving the appropriateness of prescriptions. (2) Methods: A pragmatic cluster-randomized clinical trial was conducted involving 38 family practices in Spain. Patients aged 65–74 years with multimorbidity and polypharmacy were recruited. Family physicians (FPs) were randomly allocated to continue usual care or to provide the MULTIPAP intervention based on the Ariadne principles with two components: FP training (eMULTIPAP) and FP patient interviews. The primary outcome was the appropriateness of prescribing, measured as the between-group difference in the mean Medication Appropriateness Index (MAI) score change from the baseline to the 6-month follow-up. The secondary outcomes were quality of life (EQ-5D-5 L), patient perceptions of shared decision making (collaboRATE), use of health services, treatment adherence, and incidence of drug adverse events (all at 1 year), using multi-level regression models, with FP as a random effect. (3) Results: We recruited 117 FPs and 593 of their patients. In the intention-to-treat analysis, the between-group difference for the mean MAI score change after a 6-month follow-up was −2.42 (95% CI from −4.27 to −0.59) and, between baseline and a 12-month follow-up was −3.40 (95% CI from −5.45 to −1.34). There were no significant differences in any other secondary outcomes. (4) Conclusions: The MULTIPAP intervention improved medication appropriateness sustainably over the follow-up time. The small magnitude of the effect, however, advises caution in the interpretation of the results given the paucity of evidence for the clinical benefit of the observed change in the MAI. Trial registration: Clinicaltrials.gov NCT02866799.

Background The progressive ageing of the population is leading to an increase in multimorbidity and polypharmacy, which in turn may increase the risk of hospitalization and mortality. The enhancement of care with information and communications technology (ICT) can facilitate the use of prescription evaluation tools and support system for decision-making (DSS) with the potential of optimizing the healthcare delivery process. Objective To assess the effectiveness and cost-effectiveness of the complex intervention MULTIPAP Plus, compared to usual care, in improving prescriptions for young-old patients (65-74 years old) with multimorbidity and polypharmacy in primary care. Methods/design This is a pragmatic cluster-randomized clinical trial with a follow-up of 18 months in health centres of the Spanish National Health System. Unit of randomization: family physician. Unit of analysis: patient. Population Patients aged 65–74 years with multimorbidity (≥ 3 chronic diseases) and polypharmacy (≥ 5 drugs) during the previous 3 months were included. Sample size n = 1148 patients (574 per study arm). Intervention Complex intervention based on the ARIADNE principles with three components: (1) family physician (FP) training, (2) FP-patient interview, and (3) decision-making support system. Outcomes The primary outcome is a composite endpoint of hospital admission or death during the observation period measured as a binary outcome, and the secondary outcomes are number of hospital admission, all-cause mortality, use of health services, quality of life (EQ-5D-5L), functionality (WHODAS), falls, hip fractures, prescriptions and adherence to treatment. Clinical and sociodemographic factors will be explanatory variables. Statistical analysis The main result is the difference in percentages in the final composite endpoint variable at 18 months, with its corresponding 95% CI. Adjustments by the main confounding and prognostic factors will be performed through a multilevel analysis. All analyses will be carried out in accordance to the intention-to-treat principle. Discussion It is important to prevent the cascade of negative health and health care impacts attributable to the multimorbidity-polypharmacy binomial. ICT-enhanced routine clinical practice could improve the prescription process in patient care. Trial registration ClinicalTrials.gov NCT04147130. Registered on 22 October 2019

The beneficial effects of social support on morbidity, mortality, and quality of life are well known. Using the baseline data of the MULTIPAP study (n = 593), an observational, descriptive, cross-sectional study was carried out that analyzed the sex differences in the social support perceived by polymedicated adults aged 65 to 74 years with multimorbidity. The main outcome variable was social support measured through the Duke–UNC-11 Functional Social Support (DUFSS) questionnaire in its two dimensions (confident support and affective support). For both sexes, the perception of functional social support was correlated with being married or partnered and having a higher health-related quality of life utility index. In women, it was correlated with a higher level of education, living alone, and treatment adherence, and in men with higher monthly income, prescribed drugs and fewer diagnosed diseases.

The TeNDER project aims to improve the Quality of Life (QoL) of chronic patients through an integrated care ecosystem. This study evaluates the Health Recommender System (HRS) developed for the project, which offers personalized recommendations based on data collected from a set of monitoring devices. The list of notifications covered different areas of daily-life such as physical activity, nutrition, and sleep. We conducted this case of study to evaluate the effectiveness and usability of the HRS in providing accurate and relevant recommendations to users. Evaluation process consisted on survey administration for QoL assessment, and the satisfaction and usability of the HRS. The four-week pilot study involved several patients and caregivers, and demonstrated that the HRS was perceived as user-friendly, consistent, and helpful, with a positive impact on patients’ QoL. However, the study highlights the need for improvement in terms of personalization of recommendations.

Background: Clinical practice guidelines (CPGs) have great teaching potential for health professionals in training, although their use is limited. The objective of this study was to evaluate the effectiveness and adherence to e-EDUCAGUIA teaching strategy using educational game with simulated clinical scenarios to implement a CPG on antimicrobial therapy compared to the usual dissemination strategies in improving the knowledge and skills of family medicine residents.Methods: This was a multicentre cluster-randomized clinical trial in 7 teaching units in Madrid (Spain). Intervention: educational games based on CPG recommendations, compared with the passive dissemination of the guideline. Main outcome variable: knowledge and skills questionnaire scores one month after the intervention. The difference in mean scores between the intervention and control groups at one month was determined, along with the 95% CI using generalized linear models.Results: A total of 202 residents participated (104 in the intervention group and 98 in the control group). One hundred residents performed the post-test at one month (45 in the intervention group vs. 55 in the control group). The differences favoured the intervention group in terms of both the final scores at month (11.4, 95% CI 6.9–15.9) and the change from baseline scores (11.9, 95% CI 5.9–17.9), with estimated effect sizes of 0.88 for the between-groups difference and 0.75 for the change in baseline difference. For each additional hour of training in evidence-based medicine there was a an increase of 0.28 points (95 % CI 0.15–0.42). Conclusions: The e-EDUCAGUIA strategy improves the knowledge and skills of medicine residents for clinical decision-making during short-term antimicrobial therapy. Adherence to educational games in the absence of specific incentives is moderate.Trial registration: ClinicalTrials.gov Identifier: NCT02210442. Registered 6 August 2014, https://www.clinicaltrials.gov/ct2/show/NCT02210442