Evidence in Practice - A Pilot Study Leveraging Companion Animal and Equine Health Data from Primary Care Veterinary Clinics in New Zealand.
Authors: Muellner Petra, Muellner Ulrich, Gates M Carolyn, Pearce Trish, Ahlstrom Christina, O'Neill Dan, Brodbelt Dave, Cave Nick John
Journal: Frontiers in veterinary science
Summary
# Editorial Summary Veterinary practitioners possess invaluable clinical intelligence from daily patient interactions, yet this knowledge remains largely untapped for population-level health surveillance and research. A New Zealand pilot programme tested the feasibility of extracting clinical data—presentation reasons and diagnoses—from existing computerized practice management systems across two veterinary clinics over four weeks, analysing 344 consults to create a prototype national surveillance database. Key findings revealed that whilst practice-based data capture is technically viable and valuable for establishing disease baseline incidence and identifying emerging health trends, successful implementation depends critically on intuitive system design, practitioner engagement strategies, and robust data quality assurance protocols. For equine professionals, this approach offers genuine potential to shift from retrospective case reporting to prospective, population-wide monitoring that could inform biosecurity decisions, detect unusual disease patterns early, and generate evidence for clinical decision-making across nutrition, rehabilitation and farrier practice. Scaling such a system requires balancing data security and standardisation with the workflow realities of busy mixed practices, making user experience and minimal administrative burden essential to sustaining veterinary participation.
Read the full abstract on PubMed
Practical Takeaways
- •Practice-based surveillance systems built on existing veterinary software can generate valuable population-level health data without requiring additional data entry burden if system design is intuitive.
- •Participating in standardized data capture initiatives allows individual practices to contribute to detecting disease trends and unusual patterns relevant to local animal populations.
- •Success of national surveillance networks depends heavily on system usability—if software is cumbersome, even well-intentioned practitioners will struggle with compliance.
Key Findings
- •A pilot surveillance system successfully extracted clinical data from 344 patient consults across two New Zealand veterinary clinics over 4 weeks.
- •High usability and smart interface design are critical requirements for veterinarians to engage with and submit quality data to practice-based surveillance systems.
- •Geospatial integration of multi-practice clinical data can establish baseline disease incidence, detect unusual trends, and support both infectious disease management and research activities.
- •Key challenges for scaling include ensuring sustained veterinarian engagement, maintaining data quality, and developing secure big data management infrastructure.