Reliability in performance assessment creates a potential application of artificial intelligence in veterinary education: evaluation of suturing skills at a single institution.

OBJECTIVES: To evaluate suturing skills of veterinary students using 3 common performance assessments (PAs) and to compare findings to data obtained by an electromyographic armband. SAMPLE: 16 second-year veterinary students. PROCEDURES: Students performed 4 suturing tasks on synthetic tissue models 1, 3, and 5 weeks after a surgical skills course. Digital videos were scored by 4 expert surgeons using 3 PAs (an Objective Structured Clinical Examination [OSCE]- style surgical binary checklist, an Objective Structured Assessment of Technical Skill [OSATS] checklist, and a surgical Global Rating Scale [GRS]). Surface electromyography (sEMG) data collected from the dominant forearm were input to machine learning algorithms. Performance assessment scores were compared between experts and correlated to task completion times and sEMG data. Inter-rater reliability was calculated using the intraclass correlation coefficient (ICC). Inter-rater agreement was calculated using percent agreement with varying levels of tolerance. RESULTS: Reliability was moderate for the OSCE and OSATS checklists and poor for the GRS. Agreement was achieved for the checklists when moderate tolerance was applied but remained poor for the GRS. sEMG signals did not correlate well with checklist scores or task times, but features extracted from signals permitted task differentiation by routine statistical comparison and correct task classification using machine learning algorithms. CLINICAL RELEVANCE: Reliability and agreement of an OSCE-style checklist, OSATS checklist, and surgical GRS assessment were insufficient to characterize suturing skills of veterinary students. To avoid subjectivity associated with PA by raters, further study of kinematics and EMG data is warranted in the surgical skills evaluation of veterinary students.

Encouraging Critical Clinical Thinking (CCT) Skills in First-Year Veterinary Students.

First-year didactic course instructors at the University of Illinois College of Veterinary Medicine leverage earlier clinical rotation experiences with weekly "Clinical Correlations" exercises to provide early exposure to critical clinical thinking (CCT). This study evaluated the efficacy of individual and paired group exercises on CCT development. Before and after instruction, the Cornell Critical Thinking Test (Level Z) (CCTTZ) was administered. Based on the hypothesis that students with higher scores would coach lower-scoring colleagues during group exercises, heterogeneous groups with similar mean scores were established for the year. Students completed 14 individual and paired group exercises over 6 months. Exercises were designed to increase in complexity and decline in scaffolding. Seven of the exercises were cases using the Applied Learning Platform (ALP) at http://www.whenknowingmatters.com . Student analyses were scored according to a six-category critical-thinking rubric using a 5-point scale. Consistent with our hypothesis, individual and group rubric scores increased significantly, plateauing near the end of the year. Contrary to our hypothesis, mean overall CCTTZ scores did not change, but there was a small statistically significant increase in the ability to assess the validity of an argument. Student attitudes were mixed. Positive comments focused on reinforcement of prior didactic instruction, while negative comments focused on preparation time needed to conduct research on clinical concepts, and on a lack of explicit evaluation by summative examinations. Nonetheless, end-of-year GPAs correlated linearly with cumulative individual rubric scores. In summary, the value of early curriculum CCT training was confirmed when discipline-specific criteria were applied.

The National Microbial Pathogen Database Resource (NMPDR): a genomics platform based on subsystem annotation.

The National Microbial Pathogen Data Resource (NMPDR) (http://www.nmpdr.org) is a National Institute of Allergy and Infections Disease (NIAID)-funded Bioinformatics Resource Center that supports research in selected Category B pathogens. NMPDR contains the complete genomes of approximately 50 strains of pathogenic bacteria that are the focus of our curators, as well as >400 other genomes that provide a broad context for comparative analysis across the three phylogenetic Domains. NMPDR integrates complete, public genomes with expertly curated biological subsystems to provide the most consistent genome annotations. Subsystems are sets of functional roles related by a biologically meaningful organizing principle, which are built over large collections of genomes; they provide researchers with consistent functional assignments in a biologically structured context. Investigators can browse subsystems and reactions to develop accurate reconstructions of the metabolic networks of any sequenced organism. NMPDR provides a comprehensive bioinformatics platform, with tools and viewers for genome analysis. Results of precomputed gene clustering analyses can be retrieved in tabular or graphic format with one-click tools. NMPDR tools include Signature Genes, which finds the set of genes in common or that differentiates two groups of organisms. Essentiality data collated from genome-wide studies have been curated. Drug target identification and high-throughput, in silico, compound screening are in development.