Impact of Artificial Intelligence assisted Drug Therapy Optimization on Drug related problems Amongst Elderly Patients: A Systematic Review

Abstract DRPs are associated with higher healthcare costs and hospital admissions, longer hospital stays, lower quality of life and higher mortality. Therefore, special considerations must be made when prescribing and using medicines in older patients, such as avoiding inappropriate medicines, monitoring side effects, avoiding drug-drug interactions, and assessing adherence and patient participation. In recent years, there has been increasing interest in the use of clinical decision support systems to support prescribing. Computerised interventions have been reported to be more effective than traditional educational interventions delivered by prescribers or those where a pharmacist reviewed the medication. This review critically appraises studies looking at artificial intelligence-assisted optimisation of drug therapy in hospitalized elderly patients. Following the PRISMA guidelines, we will conduct a systematic review that includes three databases: PubMed, Google Scholar and Scopus. The proposed review will include randomized, non-randomized, and cohort studies. Study types such as literature reviews, letters to the editor, pilot studies and short communications will be excluded from the review. We will summarise the available evidence on the effectiveness of computer-assisted interventions in identifying DRPs in hospitalised older patients, and the frequency, nature, and acceptance rate of computer-assisted recommendations.