Medicine identifier
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Summary
9 papers analyzed
These studies suggest that various methods, including machine learning, image classification, unique edible identifiers, and Tall-Man Lettering, can improve the accuracy and safety of medicine identification.
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Advances in Medicine Identifier Systems
Accuracy and Usability of Medication Identifiers
The accuracy and usability of medication identifiers are crucial for ensuring patient safety and effective healthcare delivery. Recent evaluations highlight the need for contemporary systems that leverage mobile and web-based technologies to accurately identify oral medications. These systems are essential for both healthcare professionals and patients to prevent medication errors and ensure proper usage.
ISO Identification of Medicinal Products (IDMP) for Herbals
The ISO Identification of Medicinal Products (IDMP) framework provides a robust system for defining substances based on their scientific identity rather than their use or production method. This approach is particularly beneficial for herbal medicines, as it uses scientific names to mitigate the health risks associated with other naming conventions.
Linguistic Approaches to Drug Name Identification
A preliminary linguistic study has explored the unique characteristics of drug names, including their readability and linguistic parameters. This research emphasizes the importance of drug nomenclature in reducing medication errors and enhancing patient safety. The study analyzed 947 medicine names, revealing diverse linguistic features that could inform better regulatory practices.
Mobile Medicine Identification for the Elderly
A mobile application has been developed to assist the elderly in identifying medications using smartphone cameras. This system, which employs image classification and text recognition technologies, has shown high accuracy rates in identifying medications from blister pack images. Such innovations are crucial in reducing medication errors among the elderly population.
Machine Learning in Drug Identification
Machine learning, particularly deep learning techniques, plays a significant role in drug identification. Systems using Support Vector Machines (SVM) and Convolutional Neural Networks (CNN) have been developed to recognize and identify drug names from images. These technologies enhance the accuracy and efficiency of drug identification processes.
CandyCodes: Unique Edible Identifiers
CandyCodes offer a novel solution to combat counterfeit medications. By applying unique, random patterns of nonpareils to each pill, manufacturers can create a database of authentic medication identifiers. Consumers can verify the authenticity of their medications using a simple cellphone camera, significantly reducing the risk of consuming counterfeit drugs.
National Drug Code (NDC) Identifiers in E-Prescribing
The use of National Drug Code (NDC) identifiers in e-prescribing is widespread, but there are concerns about the accuracy and consistency of these codes. A study analyzing e-prescriptions found that while the majority contained valid NDC numbers, a significant portion included unrepresentative or obsolete codes, which could disrupt pharmacy workflows and lead to medication errors.
Tall-Man Lettering to Prevent Medication Errors
Tall-Man Lettering (TML) is an effective strategy to reduce medication errors caused by look-alike, sound-alike (LASA) drug names. By using uppercase letters to highlight differences in similar drug names, TML helps healthcare professionals avoid confusion. A study using Levenshtein Distance, Bigram, and Trigram methods identified high-risk drug pairs for TML implementation, demonstrating its potential to enhance patient safety.
Reducing Bias and Stigma in Patient Identifiers
Efforts to reduce bias and stigma in patient identifiers have led to the development of recommendations for their use in medical education. These guidelines aim to address implicit biases in healthcare settings, ensuring that patient identifiers are used in a way that promotes equity and reduces stigma.
Conclusion
The advancements in medicine identifier systems, from mobile applications and machine learning to unique edible identifiers and standardized naming conventions, are pivotal in enhancing patient safety and reducing medication errors. These innovations, supported by rigorous research and technological development, offer promising solutions to the challenges faced in modern healthcare.
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