Analysis of call volumes to poison control centers has shown a significant increase, primarily associated with requests for pill identification. The service is available to healthcare personnel and the general public. poison control centers provide expert advice, over the telephone, with respect to possible exposure to poisonous substances, such as some prescription medications. Part of the center’s medical screening examination included medication identification by a pharmacist.Īnother aspect of patient treatment in which visual identification of pills can potentially improve care has to do with the availability of experts as part of the poison control centers system. The need to fill in missing information and identify medications is also illustrated in the operational flow of a successful evacuation center operated during the hurricane Katrina event. This is of particular concern for people with chronic conditions that may experience adverse effects with a disruption in their medication regimen. A recent literature survey identified medication loss and difficulties in filling prescriptions as common phenomena in evacuation scenarios, with evacuees only able to provide partial information about their medications. This technology is potentially usable by both healthcare personnel and the general public.įor patient care, identification of pills based on their visual appearance has the potential to facilitate improved treatment in a variety of settings, including disasters, poison control centers and patient persistence.įollowing natural or man-made disasters, it is not uncommon for pills and documentation to be separated. Visual identification is an additional technology addressing this issue, which can also be deployed outside the pharmacy for use prior to medication administration. bar code systems) to further reduce them. While dispensing error rates are low, pharmacies continue to incorporate technologies (e.g. Identification and confirmation of prescribed pills can mitigate dispensing errors. Such errors can result in adverse drug events (i.e. copyright prescription, transcription (interpretation of medication order), dispensing, and administration. Ĭorrect identification of prescription oral solid dosage forms of medication, pills, based on their visual appearance is a key step required to assure patient safety and facilitate more effective patient care.įrom a safety perspective, a variety of errors can occur across the pharmacological chain. The training dataset will continue to be freely available online at. This is an initial promising step towards development of an NLM software system and application-programming interface facilitating pill identification. In the retrieval results, the correct image was amongst the top five ranked images 43%, 12%, and 11% of the time, out of 5000 query/consumer images. Determination of the winning teams was done using the mean average precision quality metric, with the three winners obtaining mean average precision scores of 0.27, 0.09, and 0.08. Challenge submissions were required to produce a ranking of the reference images, given a consumer quality image as input. A second dataset acquired from 1000 pills with similar distributions of shape and color was reserved as a segregated testing set. A training dataset consisting of 2000 reference images and 5000 corresponding consumer quality images acquired from 1000 pills was provided to challenge participants. The data for the competition consisted of two types of images, high quality macro photographs, reference images, and consumer quality photographs of the quality we expect users of a proposed application to acquire. Potential benefits of this capability include confirmation of the pill in settings where the documentation and medication have been separated, such as in a disaster or emergency and confirmation of a pill when the prescribed medication changes from brand to generic, or for any other reason the shape and color of the pill change. This challenge was motivated by the need to easily identify unknown prescription pills both by healthcare personnel and the general public. National Library of Medicine announced a challenge competition calling for the development and discovery of high-quality algorithms and software that rank how well consumer images of prescription pills match reference images of pills in its authoritative RxIMAGE collection.
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