Evaluating the dose, indication and agreement with guidelines of antimicrobial use in companion animal practice with natural language processing

Reaching consensus amongst international experts on the use of high importance-rated antimicrobials in animals - a Delphi study

In Australia, antimicrobials are given an importance rating by the Australian Strategic and Technical Advisory Group on antimicrobial resistance. High importance antimicrobials are those essential for the treatment or prevention of infections in humans, where there are few or no treatment alternatives. In this study we consulted with experts from across human and animal health using the Delphi consensus-building process to establish the circumstances under which antimicrobials with high importance to human health could be used in animals in Australia. We used three rounds of online surveys. Group responses were provided to participants in each subsequent round to facilitate convergence of opinion. Consensus was defined as 80 % or more of respondents selecting the same option for a question. By the end of the third round, consensus was achieved on eight items. This included the use of high importance antimicrobials being appropriate if culture and sensitivity testing indicated the organism was resistant to low- and medium-rated antimicrobials that could be used to treat the case. If any high-importance antimicrobials are prescribed for animals there was also agreement that a clear indication for this use and justification for antimicrobial choice must be recorded in the medical history, along with the dose rate, route of administration, the duration and the time point for review of the condition and associated antimicrobial therapy. Appropriateness of use of high importance antimicrobials in critically ill animals where culture and sensitivity results are not available is still undefined. Further work is also required to establish which particular organisation should be notified of the use of high importance antimicrobials not registered for use in animals. The Delphi process was valuable in facilitating consensus amongst international experts from a broad range of health backgrounds and experience.

Using natural language processing and patient journey clustering for temporal phenotyping of antimicrobial therapies for cat bite abscesses

BACKGROUND

Temporal phenotyping of patient journeys, which capture the common sequence patterns of interventions in the treatment of a specific condition, is useful to support understanding of antimicrobial usage in veterinary patients. Identifying and describing these phenotypes can inform antimicrobial stewardship programs designed to fight antimicrobial resistance, a major health crisis affecting both humans and animals, in which veterinarians have an important role to play.

OBJECTIVE

This research proposes a framework for extracting temporal phenotypes of patient journeys from clinical practice data through the application of natural language processing (NLP) and unsupervised machine learning (ML) techniques, using cat bite abscesses as a model condition. By constructing temporal phenotypes from key events, the relationship between antimicrobial administration and surgical interventions can be described, and similar treatment patterns can be grouped together to describe outcomes associated with specific antimicrobial selection.

METHODS

Cases identified as having a cat bite abscess as a diagnosis were extracted from VetCompass Australia, a database of veterinary clinical records. A classifier was trained and used to label the most clinically relevant event features in each record as chosen by a group of veterinarians. The labeled records were processed into coded character strings, where each letter represents a summary of specific types of treatments performed at a given visit. The sequences of letters representing the cases were clustered based on weighted Levenshtein edit distances with KMeans+ + to identify the main variations of the patient treatment journeys, including the antimicrobials used and their duration of administration.

RESULTS

A total of 13,744 records that met the selection criteria was extracted and grouped into 8436 cases. There were 9 clinically distinct event sequence patterns (temporal phenotypes) of patient journeys identified, representing the main sequences in which surgery and antimicrobial interventions are performed. Patients receiving amoxicillin and surgery had the shortest duration of antimicrobial administration (median of 3.4 days) and patients receiving cefovecin with no surgical intervention had the longest antimicrobial treatment duration (median of 27 days).

CONCLUSION

Our study demonstrates methods to extract and provide an overview of temporal phenotypes of patient journeys, which can be applied to text-based clinical records for multiple species or clinical conditions. We demonstrate the effectiveness of this approach to derive real-world evidence of treatment impacts using cat bite abscesses as a model condition to describe patterns of antimicrobial therapy prescriptions and their outcomes.

The potential application of artificial intelligence in veterinary clinical practice and biomedical research

Artificial intelligence (AI) is a fast-paced technological advancement in terms of its application to various fields of science and technology. In particular, AI has the potential to play various roles in veterinary clinical practice, enhancing the way veterinary care is delivered, improving outcomes for animals and ultimately humans. Also, in recent years, the emergence of AI has led to a new direction in biomedical research, especially in translational research with great potential, promising to revolutionize science. AI is applicable in antimicrobial resistance (AMR) research, cancer research, drug design and vaccine development, epidemiology, disease surveillance, and genomics. Here, we highlighted and discussed the potential impact of various aspects of AI in veterinary clinical practice and biomedical research, proposing this technology as a key tool for addressing pressing global health challenges across various domains.