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Understanding veterinary practitioners' decision-making process: implications for veterinary medical education
Jean-Michel Vandeweerd1, Solène Vandeweerd, Catherine Gustin
1Department of Veterinary Medicine, University of Namur, Namur, Belgium. jean-michel.vandeweerd@fundp.ac.be
Journal of Veterinary Medical Education
|June 22, 2012
Summary
Veterinary surgeons often bypass evidence-based medicine (EBM), relying on colleagues and the internet over scientific literature due to time constraints. Training and better tools are recommended to improve clinical decision-making.
Area of Science:
- Veterinary Medicine
- Clinical Decision-Making
- Information Science
Background:
- Understanding veterinary clinical decision-making is crucial for enhancing animal care, client satisfaction, and veterinary education.
- Private practitioners' processes for making clinical decisions require further investigation to identify areas for improvement.
Purpose of the Study:
- To explore and understand the decision-making processes employed by private veterinary practitioners.
- To identify the factors influencing clinical decisions in veterinary practice.
Main Methods:
- A qualitative approach using grounded theory was employed.
- Data collection involved telephone surveys and semi-structured face-to-face interviews with veterinary practitioners.
Main Results:
- A decision-making framework was identified, including two decision processes, five case management steps, and three influencing factors.
- Veterinary surgeons infrequently utilize the evidence-based medicine (EBM) approach, preferring consultation with colleagues, specialists, and online resources over scientific literature due to time limitations.
Conclusions:
- Veterinary practitioners often do not prioritize evidence-based medicine (EBM) due to time constraints, relying on informal information sources.
- There is a need for educational interventions in veterinary schools to enhance decision-making skills.
- Improved access to and training in the use of evidence-based information and tools are necessary to optimize clinical decision-making and information retrieval efficiency.
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