Medication Optimization for Multimorbidity: Evidence, Decisions, and Digital Enablement

Population aging and shifting disease patterns have made multimorbidity — the co-occurrence of two or more chronic conditions in a single patient — the norm rather than the exception. Roughly one-third of adults globally, and more than half of older adults, live with multimorbidity, while the prevalence among adults aged 60 and above in China now exceeds 50%. Multimorbidity almost inevitably drives polypharmacy, commonly defined as the concurrent use of five or more medications, which affects 30%–60% of adults over 65. Polypharmacy substantially raises the risk of drug-drug interactions, adverse drug events, prescribing cascades, medication non-adherence, and hospital readmission — nearly half of multimorbid patients present with potential drug interactions, and roughly 30% of adverse drug events are attributable to them.Yet most current clinical guidelines and their supporting evidence remain built on single-disease frameworks. The randomized controlled trials that inform guideline recommendations routinely exclude multimorbid and frail older patients, leaving clinicians with guidelines that lack applicable evidence and recommendations that are difficult to implement in real-world, complex-care settings. Medication management for multimorbidity urgently needs methodological innovation and new models of intervention. At the same time, digital and intelligent technologies — including clinical decision support systems, electronic health record mining, and AI-assisted prescribing — are beginning to reshape how medication regimens for multimorbid patients are optimized.This Research Topic focuses on two pillars: evidence generation and digital enablement. We welcome original research, systematic reviews, and methodological innovations that advance medication therapy management for multimorbidity, with the goal of moving beyond single-disease guidelines toward a person-centered, evidence-driven, and digitally enabled paradigm for medication optimization.We invite submissions addressing, but not limited to, the following themes:Evidence generation for medication management in multimorbid and frail populations, including pragmatic trials, real-world evidence, and methodological approaches to overcome the exclusion of complex patients from conventional RCTsClinical decision-making frameworks for polypharmacy, deprescribing, and prescribing cascades in multimorbid patientsDrug-drug interaction and adverse drug event prediction, detection, and mitigation strategiesDigital health tools, clinical decision support systems, and AI/machine learning applications for medication optimization in multimorbidityElectronic health record-based and data-driven approaches to identifying and managing high-risk polypharmacy patientsPerson-centered and shared decision-making models for medication management across multiple chronic conditionsHealth system, policy, and implementation strategies to translate evidence and digital tools into routine multimorbidity care Topic editors: Pengxiang Zhou, Li-Chia Chen, Yang Zhao Source: https://www.frontiersin.org/research-topics/86822/medication-optimization-for-multimorbidity-evidence-decisions-and-digital-enablement