Leader: Enrica Menditto; Other collaborator(s): Lara Perrella, Valentina Orlando, Sara Mucherino
Medication adherence is a critical issue affecting older adults. On average, 30-50% of prescribed medications are not taken as directed. Non-adherence to medications negatively impacts patient health, leads to increased healthcare utilization, and represents a significant barrier to realizing the full benefits of evidence-based therapies. The economic consequences of non-adherence are also considerable. In Europe alone, non-adherence is linked to nearly 200,000 deaths annually and accounts for €125 billion in potentially preventable direct and indirect costs. To address this societal challenge, interventions to improve medication adherence, including the use of innovative technologies, must be integrated into routine clinical practice to enhance health outcomes and healthcare system efficiency. As the population ages, a growing proportion of individuals are affected by multiple chronic conditions, a phenomenon known as multimorbidity, which consumes 70% of healthcare costs. The treatment of these comorbidities often results in polypharmacy. It is estimated that 11% of unplanned hospital admissions are due to medication-related harm, with over 70% of these admissions involving elderly patients on polypharmacy. To investigate medication-taking behaviors in real-world scenarios, we will employ drug utilization approaches, utilizing various health-related automated databases as tools in the research outlined in WP3.
Brief description of the activities and of the intermediate results:
Addresses the secondary use of data to develop targeted interventions in specific health domains, focusing primarily on medication adherence among older adults, which is a critical issue due to its negative impact on health outcomes and healthcare costs. Activities have included the monitoring of rational medication use and the development of an AI-based algorithm to identify adherence trajectories. Key results include the successful application of the AI algorithm to heart failure treatments. The research has provided valuable insights into adherence patterns and their association with polypharmacy and multimorbidity.
Main policy, industrial and scientific implications
From a policy perspective, this research is vital for addressing the issue of non-adherence among patients older than 65 years of age, which contributes to preventable healthcare costs and hospital admissions. Implementing data-driven interventions can improve medication management and patient outcomes, reducing the strain on healthcare systems. Industrially, the development of AI-based tools for monitoring medication adherence presents opportunities for innovation in health technology, enhancing healthcare efficiency. Scientifically, the task advances the understanding of adherence patients’ patterns and factors associated with them in patients with heart failure (HF).
Brief description of the activities and of the intermediate results
A multi-faceted approach and the interdisciplinary collaboration among researchers, healthcare providers, policymakers, and technology developers are needed to address the growing challenge of polypharmacy in aging populations. Key results include a systematic review on polypharmacy management in Italy. Ultimately, such efforts will contribute to more sustainable healthcare systems and better outcomes for elderly patients.
Main policy, industrial and scientific implications
From a clinical perspective, the understanding of polypharmacy in older adults provides crucial insights into the challenges associated with managing frailty patients. Scientifically, the task advances the understanding of polypharmacy by providing the fundamentals for implementing personalized interventions for treatment optimization in patients over 65 of age with multimorbid conditions and implementing knowledge and appropriateness of prescription and use of medicines.
Brief description of the activities and of the intermediate results:
Addresses the secondary use of data to identify crucial gaps in poor medication adherence among older adults. Activities have included the monitoring of rational medication use and analysis of specific factors involved. Key results include ongoing studies on the correlation between falls and specific medications. The research has provided valuable insights into adherence patterns and their association with polypharmacy and multimorbidity.
Main policy, industrial and scientific implications:
From a policy perspective, this research provides a solid scientific basis for managing factors that negatively impact the healthcare system by addressing the issue of non-adherence among patients over the age of 65. A multi-faceted approach underscores the need for interdisciplinary collaboration among researchers, healthcare providers, policymakers, and technology developers to address the growing challenge of polypharmacy in aging populations. Ultimately, such efforts will contribute to more sustainable healthcare systems and better outcomes for older patients. Scientifically, the task advances the understanding of specific patterns of more-at-risk patients, as drugs that increase the risk of falls.
Brief description of the activities and of the intermediate results:
Falls are a leading cause of hospitalization among older adults, strongly affecting quality of life. Fall-Risk-Increasing Drugs (FRIDs) represent a key modifiable risk factor, yet their role in fall-related hospitalizations requires further investigation. Drug Utilization approaches represent a unique opportunity to improve understanding of the complexity of FRIDs prescribing in frail patients, leading to risk minimization measures.
Main policy, industrial and scientific implications:
From a policy perspective, this research provides findings to implement strategies that optimize prescribing and reduce fall-related hospitalizations, improving healthcare sustainability. Scientifically, the study advances understanding of fall-risk-increasing drugs (FRIDs), showing their strong link to hospitalizations. It underscores the need for interdisciplinary collaboration to refine prescribing guidelines and manage polypharmacy effectively. These insights support evidence-based policies and innovation in medication safety, ultimately enhancing health outcomes for aging populations while reducing healthcare system burdens.
Brief description of the activities and of the intermediate results:
Task 3.3 continued to investigate the role of Fall-Risk-Increasing Drugs (FRIDs) in fall-related hospitalizations among older adults. A nested case-control study using administrative data from two Italian regions confirmed that FRID use—especially opioids and antidepressants—is significantly associated with increased risk of hospitalization due to falls. Risk was highest with prolonged and recent use. These findings contribute to a deeper understanding of FRID prescribing patterns and their impact on frail, multimorbid patients.
Main policy, industrial and scientific implications:
The study provides strong evidence to support targeted prescribing strategies and medication management in older populations. It informs national policies aiming to reduce avoidable hospitalizations and improve prescribing appropriateness. The results also support the development of data-driven policies for clinical decision-making, advancing innovation and patient safety in medication use, helping to improve health outcomes in older populations to reduce healthcare system burdens.
Brief description of the activities and of the intermediate results:
Task 3.3 advanced secondary use of healthcare data by integrating psychosocial determinants into analyses of healthcare utilisation and medication use. A multicentre cross-sectional study in Spain examined primary care data from nine autonomous communities.
Personality traits, assessed with the BFI-10, were analysed in relation to healthcare utilisation and polypharmacy. Results indicated that extraversion and conscientiousness were linked to higher primary care use, while neuroticism was associated with polypharmacy. These findings build on previous research by identifying psychosocial factors relevant to healthcare-seeking behaviour and medication management.
Main policy, industrial and scientific implications:
From a policy perspective, these results support patient-centred strategies in primary care that incorporate behavioural factors to optimise service use and medication management for multimorbid populations. Scientifically, the task strengthens evidence on the role of non-clinical determinants in healthcare utilisation and polypharmacy, supporting targeted interventions using secondary data. Industrially, the findings may inform development of digital decision-support and AI-based risk stratification tools that integrate psychosocial variables.
Brief description of the activities and of the intermediate results:
Task 3.3 further analysed secondary healthcare data using sex-stratified and subgroup analyses to identify differences in healthcare utilisation and medication use. Multivariate models applied to the Spanish multicentre dataset revealed sex-specific associations between personality traits and healthcare use.
In men, extraversion was associated with more nursing visits, and openness was linked to greater emergency service use and medication consumption. In women, extraversion and conscientiousness were associated with greater general practitioner use, while conscientiousness was inversely associated with hospitalisation. Agreeableness was associated with polypharmacy in women.
Main policy, industrial and scientific implications:
From a policy perspective, identifying sex-specific utilisation patterns supports tailored preventive and management strategies in primary care. Scientifically, these results highlight the importance of integrating psychosocial variables into pharmacoepidemiological and health services research. Industrially, the findings may help refine predictive models and digital health solutions for personalised care and rational prescribing.
Brief description of the activities and of the intermediate results:
Task 3.3 consolidated evidence from secondary analyses of large-scale primary care data to inform targeted interventions on healthcare utilisation, polypharmacy, and medication-related risks. Integrating personality traits with clinical and sociodemographic variables enabled the identification of patient profiles with higher healthcare use and increased polypharmacy risk.
Results confirm that personality traits independently influence patterns of healthcare utilisation and medication use, in addition to established clinical determinants. These findings complement earlier Task 3.3 activities on medication adherence and fall-risk-increasing drugs, supporting the identification of modifiable risk factors in ageing and multimorbid populations.
Main policy, industrial and scientific implications:
From a policy perspective, the findings support the implementation of integrated, data-driven approaches in primary care that address both clinical and psychosocial determinants of healthcare utilisation and prescribing. Scientifically, Task 3.3 demonstrates the value of incorporating psychological constructs into secondary data analyses for targeted interventions. Industrially, these results support the development of AI-based decision-support systems and personalised care models to improve medication management and health outcomes in ageing populations.
Pubblications:
Mucherino S, Lelia Dima A, Coscioni E, Vassallo MG, Orlando V and Menditto E. Longitudinal trajectory modeling to assess adherence to Sacubitril/Valsartan among patients with Heart Failure. 2023. Pharmaceutics (MDPI). (Published on 1 November 2023)
Oral at Conferences:
Perrella L, Olmastroni E, Mucherino S, Orlando V, Casula M, Menditto E. – Title: “Impatto dei farmaci e il rischio di cadute nei soggetti over 65: uno studio caso-controllo in Italia” - XXXIV Seminario Nazionale “LA VALUTAZIONE DELL’USO E DELLA SICUREZZA DEI FARMACI: ESPERIENZE IN ITALIA”, Rome, Italy, December 10, 2025.
Perrella L, Olmastroni E, Mucherino S, Orlando V, Casula M, Menditto E. – Title: “Impact of Fall-Risk-Increasing Drugs on accidental falls and injuries among community-dwelling older adults: an Italian case-control study” – 2nd General Meeting Age-It, Naples, Italy, October 29-31, 2025.
Perrella L, Olmastroni E, Mucherino S, Orlando V, Casula M, Menditto E. – Title: “Impact of Fall-Risk-Increasing Drugs on accidental falls and injuries among older adults: an Italian case-control study” - EuroDURG 2025, Uppsala, Sweden, July 1-4, 2025.
Perrella L, Olmastroni E, Mucherino S, Casula M, Illario M, Orlando V, Casula M, Menditto E. – Title: Impatto dei farmaci che aumentano il rischio di caduta negli over 65: uno studio caso-controllo in Italia” –AIE – Salerno, 8-11 April 2025
Perrella L, Mucherino S, Casula M, Illario M, Orlando V, Menditto E. Management of polypharmacy in Italy: a systematic literature review. Age-It Conference, Venezia, 20-22 May 2024
Perrella L, Mucherino S, Casula M, Illario M, Orlando V, Menditto E. Polypharmacy management in chronic conditions: a systematic literature review of Italian interventions. ESPACOMP Annual Meeting – Napoli, 21-22 November 2024.
Poster at Conferences:
Perrella L, Mucherino S, Casula M, Illario M, Orlando V, Menditto E. Polypharmacy management in chronic conditions: a systematic literature review of Italian interventions. SIF Conference, Sorrento 13-16 November 2024.
Perrella L, Mucherino S, Casula M, Illario M, Orlando V, Menditto E. Polypharmacy management in chronic conditions: a systematic literature review of Italian interventions. ESPACOMP Annual Meeting, Napoli, 21-22 November 2024.