Race-Level Reporting of Incidents Using an Online System during Three Seasons (2019/2020-2021/2022) of Thoroughbred Flat Racing in New Zealand.
Authors: Gibson Michaela J, Legg Kylie A, Gee Erica K, Rogers Chris W
Journal: Animals : an open access journal from MDPI
Summary
# Editorial Summary: Race-Level Incident Reporting in New Zealand Thoroughbred Racing New Zealand's racing industry upgraded from paper-based to digital incident reporting ('Infohorse database') in 2019, prompting researchers to evaluate whether this transition improved data quality and injury monitoring across three seasons (2019/20–2021/22). The online system significantly reduced data entry errors, particularly horse misidentification (down to 0.1%), whilst enhanced prompts and clearer definitions encouraged more frequent non-incident examinations and standardised recording of clinical findings. Musculoskeletal fractures remained stable at 0.5 per 1000 starts, consistent with historical data, though the digital platform captured a notably higher frequency of 'no observable abnormalities detected' outcomes, reflecting more systematic pre-race and post-race veterinary screening by stipendiary stewards. For equine professionals involved in racing, this structured dataset establishes a reliable foundation for identifying genuine risk factors and trends—rather than data artefacts—that can inform evidence-based management decisions affecting track design, race conditions, and welfare protocols. The shift to digital reporting demonstrates how systematic data governance enables the industry to discharge its duty of care responsibly and target interventions where they're genuinely needed.
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Practical Takeaways
- •Digital incident reporting systems significantly reduce administrative errors and improve data quality for injury surveillance in racing operations.
- •Routine screening by stipendiary stewards (reflected in NOAD reporting) plays an important preventative role in identifying issues before they become clinical problems.
- •Accurate, structured injury data collection is essential for identifying risk factors and implementing evidence-based welfare improvements in racing.
Key Findings
- •Implementation of an online reporting system (Infohorse database) reduced horse identification miscoding to 0.1% compared to the previous paper-based system.
- •Musculoskeletal fractures occurred at a rate of 0.5 per 1000 starts (95% CI = 0.3-0.6), consistent with previously reported data.
- •The online system increased frequency of non-incident examinations and 'no observable abnormalities detected' (NOAD) reporting, reflecting improved stipendiary steward screening protocols.
- •Structured digital data collection enables evidence-based monitoring of incidents and injuries to support racehorse and jockey welfare decision-making.