Evidence-Based Veterinary Information in Modern Practice: A Critical Review of Principles, Resources, Decision-making and Implementation
P. L. Sujatha *
Madras Veterinary College, Chennai-600 007, Tamil Nadu, India.
D. Ramasamy
College of Food and Dairy Technology, Chennai-600 052, Tamil Nadu, India.
R. Venkataramanan
Madras Veterinary College, Chennai-600 007, Tamil Nadu, India.
K. Anbu Kumar
Madras Veterinary College, Chennai-600 007, Tamil Nadu, India.
S. P. Preetha
Madras Veterinary College, Chennai-600 007, Tamil Nadu, India.
P. Devendran
Madras Veterinary College, Chennai-600 007, Tamil Nadu, India.
*Author to whom correspondence should be addressed.
Abstract
Evidence-based veterinary medicine depends on more than access to scientific papers. It requires clinicians to convert case uncertainty into answerable questions, retrieve relevant information from a fragmented literature, judge methodological validity and applicability, integrate research with professional expertise and owner circumstances, and evaluate whether resulting decisions improve care. This critical narrative review examines the principles, information resources and practical use of evidence-based veterinary information across companion-animal, farm-animal and broader veterinary settings. Literature was selected through live searches of PubMed/MEDLINE and Semantic Scholar, supplemented by targeted scholarly web retrieval, citation chaining and verification of bibliographic records. The synthesis focuses on work published from January 1998 to 9 June 2026, while retaining earlier foundational evidence where conceptually necessary. The evidence shows durable progress in question formulation, veterinary-specific reporting guidance, critically appraised topics, information literacy education, shared decision-making and quality improvement. At the same time, several structural constraints remain. Veterinary evidence is unevenly distributed across species and specialties, indexing is incomplete across any single database, access and time barriers shape clinicians' search behaviour, and study design or reporting weaknesses often limit confidence and transferability. Survey and qualitative research indicates that veterinarians frequently rely on colleagues, general web search and abbreviated article sections, which can be efficient but may bypass critical appraisal. Emerging clinical decision support and artificial intelligence could reduce retrieval and synthesis burden, yet their value depends on transparent provenance, current source verification, external validation and governance. The central implication is that evidence-based veterinary information should be treated as an end-to-end decision process rather than a hierarchy of publications. Sustainable implementation therefore requires linked competencies in searching, appraisal, communication, local outcome measurement and organisational learning.
Keywords: Evidence-based veterinary medicine, critical appraisal, clinical decision-making, information retrieval, knowledge translation, quality improvement