In an effort to increase access to contraception, the pharmacist scope of practice is being expanded to allow prescribing. While this is being accomplished in the United States by a variety of models, legislation that allows pharmacists to prescribe hormonal contraception under a statewide protocol is the most common. This study was designed to explore the outlooks of pharmacists regarding prescribing contraception in the period following the first state legislation and prior to statewide protocol development and availability. A qualitative study of community pharmacists in California using structured phone interviews explored their opinions regarding access to contraception in pharmacies and outlooks regarding prescribing. Data were analyzed using an inductive approach to identify themes. Among the thirty participants, the majority worked in a chain pharmacy. Themes were identified in five overarching domains: Pharmacist barriers, system barriers, patient issues, safety concerns, and pharmacist role. Most were unfamiliar with the new law, yet were interested in expanding access for patient benefit despite foreseeing challenges with implementing the service in community pharmacies. Barriers will need to be addressed and requisite training disseminated widely to facilitate successful implementation and thus improve access on a broad scale. Further research following protocol implementation is needed to understand service implementation, as well as patient utilization and satisfaction.

Extra-label drug use in food animal medicine is authorized by the US Animal Medicinal Drug Use Clarification Act (AMDUCA), and estimated withdrawal intervals are based on published scientific pharmacokinetic data. Occasionally there is a paucity of scientific data on which to base a withdrawal interval or a large number of animals being treated, driving the need to test for drug residues. Rapid assay commercial farm-side tests are essential for monitoring drug residues in animal products to protect human health. Active ingredients, sensitivity, matrices, and species that have been evaluated for commercial rapid assay tests are typically reported on manufacturers' websites or in PDF documents that are available to consumers but may require a special access request. Additionally, this information is not always correlated with FDA-approved tolerances. Furthermore, parameter changes for these tests can be very challenging to regularly identify, especially those listed on websites or in documents that are not publicly available. Therefore, artificial intelligence plays a critical role in efficiently extracting the data and ensure current information. Extracting tables from PDF and HTML documents has been investigated both by academia and commercial tool builders. Research in text mining of such documents has become a widespread yet challenging arena in implementing natural language programming. However, techniques of extracting tables are still in their infancy and being investigated and improved by researchers. In this study, we developed and evaluated a data-mining method for automatically extracting rapid assay data from electronic documents. Our automatic electronic data extraction method includes a software package module, a developed pattern recognition tool, and a data mining engine. Assay details were provided by several commercial entities that produce these rapid drug residue assay tests. During this study, we developed a real-time conversion system and method for reflowing contents in these files for accessibility practice and research data mining. Embedded information was extracted using an AI technology for text extraction and text mining to convert to structured formats. These data were then made available to veterinarians and producers via an online interface, allowing interactive searching and also presenting the commercial test assay parameters in reference to FDA-approved tolerances.

No abstract

No abstract