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Ability of a bovine transrectal palpation objective structured clinical examination to predict veterinary students' pregnancy diagnosis accuracy.

Annett AnnandaleGeoffrey Theodore FosgateHarold BokDietmar E Holm
Published in: The Veterinary record (2019)
Bovine pregnancy diagnosis (PD) by transrectal palpation (TRP) is one of the most frequently performed procedures in bovine practice, and an important competency for veterinary graduates. It is currently not known if pre-existing TRP skills on non-pregnant cows can be used to predict students' future PD accuracy. The study objective was to evaluate if TRP objective structured clinical examination (OSCE) scores can predict students' future PD accuracy.Fourth year (of a six-year programme) veterinary students (n=128) received TRP and PD training on Breed'n Betsy (BB) simulators and live cows. Students' TRP skills were assessed using a live cow TRP OSCE after completion of the fourth year training. The same students received additional TRP (BB and live cows) and PD (BB) training sessions in the first semester of their fifth year. PD accuracy was assessed after the additional TRP and PD training, five months after the TRP OSCE assessment and measured as sensitivity and specificity (the ability to correctly identify the presence and absence of pregnancy, respectively). Each student palpated six cows transrectally to diagnose pregnancy status and stage for the PD assessment. The TRP OSCE results were analysed as predictors for students' PD accuracy.Students with 'competent palpation skills' on the TRP OSCE had higher PD specificity. The individual OSCE components that were predictive of higher PD accuracy were students' ability to estimate ovarian size, identify uterine position and exclude intrauterine fluid. It was concluded that a TRP OSCE has the ability to predict students' future PD accuracy.
Keyphrases
  • high school
  • healthcare
  • primary care
  • randomized controlled trial
  • pregnant women
  • pregnancy outcomes
  • medical students
  • quality improvement
  • virtual reality
  • double blind