Perrella, Lara (2026) Polypharmacy patterns in older adults: an innovative Drug Utilisation model applied to Real-World Data. [Tesi di dottorato]

Documento PDF PhD_Thesis_XXXVIII_cycle_Perrella_Lara.pdf Visibile a [TBR] Amministratori dell'archivio Download (3MB) | Richiedi una copia

Abstract

Population ageing is a major demographic challenge of the 21st century, significantly impacting healthcare systems. Older adults often experience multimorbidity, leading to polypharmacy. Although using multiple medications may be clinically appropriate, polypharmacy increases the risk of inappropriate prescribing, adverse drug reactions, drug–drug interactions, reduced medication adherence, and higher healthcare use and costs. This PhD thesis investigated polypharmacy patterns in older adults using a novel drug utilisation model applied to real-world data. The main objective was to generate real-world evidence to improve understanding of prescribing practices, identify medication-related predictive risks, and support patient-centred strategies for safer, sustainable care in ageing populations. A stepwise methodological approach was adopted. Stage 1 mapped and critically evaluated existing interventions for polypharmacy management, focusing on the Italian healthcare setting. Systematic literature reviews and a national survey of general practitioners revealed limited implementation of structured management strategies, varied deprescribing approaches, and organisational, cultural, and clinical barriers influencing prescribing decisions. Stage 2 focused on identifying and modelling medication-related risks using real-world Electronic Healthcare Databases. Drug Utilisation indicators, including the Multisource Comorbidity Score, Anticholinergic Cognitive Burden, and Sedative Load, were used to characterise prescribing patterns and examine associations with adverse outcomes, such as falls. Advanced analytical methods supported risk stratification and pattern recognition in different older populations. Stage 3 was conducted in collaboration with the PRISMA Research Group of the Parc Sanitari Sant Joan de Déu in Barcelona, Spain. This phase focused on patient-related determinants, examining personality traits and behavioural profiles as potential predictors of healthcare service utilisation patterns and polypharmacy among adults attending primary healthcare centres. Overall, this thesis demonstrates that integrating Drug Utilisation research with Real World Data and Machine Learning provides valuable insights into the complexity of polypharmacy in older adults. The findings support the development of data-informed, patient-centred interventions to optimise prescribing, promote appropriate polypharmacy management, and improve clinical outcomes, while contributing to the sustainability of healthcare systems in ageing societies.

Downloads

Actions (login required)

Modifica documento