Background: Medical errors pose significant risks to patient safety and public health. Automated unit dose drug dispensing systems (UDDSs) have emerged as valuable tools to reduce medication errors while optimising economic and logistical resources.
Objectives: This systematic review aims to evaluate studies specifically focused on the impact of automated UDDSs in reducing medication errors and streamlining processes.
Methods: A literature search was performed on PubMed, Scopus, and Web of Science, focusing on peer-reviewed articles published between 2019 and 2024. The search, concluded on 24 September 2024, included studies conducted in inpatient hospital settings that assessed automated UDDS effects on medication errors, therapy management and inventory control. Outcomes examined included effects on patient safety, cost-effectiveness and inventory management. Results were synthesised qualitatively.
Results: From 3346 references, four studies met the inclusion criteria: a cost-effectiveness analysis, an uncontrolled before-and-after study, and two observational studies. UDDS improved medication processes, reducing drug-related problems, medication handling and dispensing time by 50% per patient per day. Integrated with barcode scanning, UDDS lowered medication administration errors (MAEs) from 19.5% to 15.8% and harmful MAEs from 3.0% to 0.3%. Overall, medication errors dropped by 45-70%, enhancing safety and reducing manual handling risks. UDDS demonstrated cost-effectiveness by significantly reducing MAEs. The study estimated a reduction in MAEs, with a cost-effectiveness ratio of €17.69 per avoided MAE. For potentially harmful MAEs, the cost-effectiveness ratio was estimated at €30.23 per avoided error. These findings suggest substantial long-term savings potential, though the exact magnitude may vary depending on hospital size and implementation specifics CONCLUSIONS: Automated UDDSs improve patient safety by significantly reducing medication errors and delivering cost savings through better inventory management. Challenges such as high initial costs and workflow adjustments can be mitigated through gradual implementation and staff training. Further integration with other healthcare technologies, such as barcoding, real-time tracking, artificial intelligence (AI)-driven error prevention tools and fully automated restocking systems could enhance UDDS benefits and further support hospital processes.
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http://dx.doi.org/10.1136/ejhpharm-2024-004444 | DOI Listing |
J Epidemiol Glob Health
March 2025
Precision Medicine Research Center, Sichuan Provincial Key Laboratory of Precision Medicine and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.
Background: Older outpatients face a heightened risk of potentially inappropriate prescribing (PIP). However, there is a paucity of evidence evaluating PIP in older outpatients attending surgical outpatient departments in China using Chinese-specific criteria. This study aimed to assess the prevalence of PIP and identify associated factors within this population.
View Article and Find Full Text PDFInt J Pharm Pract
March 2025
Griffith University School of Pharmacy and Medical Science, 1 Parklands Drive, Southport, QLD 4215, Australia.
Objective: This study explored community pharmacists' experiences and perceptions of information transfer from Queensland health hospitals for patients during transitions of care and the current utilization of electronic medical records for accessing patient information.
Methods: Qualitative methodology was used involving in-depth semi-structured interviews with community pharmacists to explore their experiences and perceptions with information transfer during patients' transitions of care. Purposive sampling was used to ensure the participation of community pharmacists who had experience with the medication management of patients discharged from Queensland health hospitals.
J Opioid Manag
March 2025
SA Pharmacy, Government of South Australia, Adelaide, Australia. ORCID: https://orcid.org/0000-0003-4786-022X.
Introduction: Chronic pain is a leading cause of chronic disease in Australia, with a 2020 report indicating that one in five Australians aged over 45 experience chronic pain. The high prevalence of chronic pain accounts for significant healthcare utilization and associated costs, with the economic impact of chronic pain estimated to be AUD$139 billion in 2018.
Case Presentations: This paper uses two exemplar cases to demonstrate inadequacies within the current systems supporting those with chronic pain and the associated impacts these inadequacies have on patient outcomes and healthcare costs.
Medicine (Baltimore)
March 2025
College of Pharmacy, Nanchang Medical College, Nanchang, Jiangxi, China.
With the development of information and communication technology, it has become possible to improve pharmacy management system (PMS) using these technologies. Our study aims to enhance the accuracy of drug attribute classification and recommend appropriate medications to improve patient compliance and treatment outcomes through the use of a semi-supervised learning method combined with artificial intelligence (AI) technology. This study proposed a semi-supervised learning method that integrates various technologies such as PMS, electronic prescriptions, and inventory management with AI to process and analyzed drug data, which enabled dynamic inventory updates and precise drug distribution.
View Article and Find Full Text PDFJAMA Netw Open
March 2025
Department of Emergency Medicine, Massachusetts General Hospital, Harvard Medical School, Boston.
Importance: Given that older adults are at high risk for adverse drug events (ADEs), many geriatric medication programs have aimed to optimize safe ordering, prescribing, and deprescribing practices.
Objective: To identify emergency department (ED)-based geriatric medication programs that are associated with reductions in potentially inappropriate medications (PIMs) and ADEs.
Data Sources: A systematic search of Scopus, Embase, PubMed, PsycInfo, ProQuest Central, CINAHL, AgeLine, and Cochrane Library was conducted on February 14, 2024, with no date limits applied.
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