Keynote Message

Illness in pet animals impacts both on their welfare, and that of their owners and wider public. Despite the size of these populations, they have become information-poor due to the historical lack of centralised data collection. Projects like the Small Animal Veterinary Surveillance NETwork (SAVSNET - University of Liverpool) and VetCompass (Royal Veterinary College) seek to fill this gap using Health Informatics, which allows electronic health records (EHRs) to be anonymised and used for research. Both projects are collecting EHRs at scale to better understand the real world of companion animal clinical veterinary practice.

Both projects have assembled a strong coalition of collaborators and data partners allowing the collection of real-time data from sentinel networks of veterinary clinics (both projects) and diagnostic laboratories (SAVSNET) across the UK.

The use of these unique and rich data sources has rapidly grown. Key areas of current research include antimicrobial resistance mapping, description of antibacterial prescription, as well as real-time outbreak monitoring in both animal-only and "one health" settings. Using text-mining approaches, we are unlocking the surveillance value previously hidden in the clinical narrative of each EHR, opening new opportunities for surveillance (clinical signs, ticks), and pointing to a future that is less reliant on practitioner coding. Through the owner postcode, we are linking EHRs to other data sources and understanding the impact of climate and owner-predicted deprivation on disease and treatment.

SAVSNET has also created innovative and novel feedback loops that provide bespoke results to our data partners, increasingly in real-time. This allows for the first-time practitioners partaking in this surveillance to benchmark their own data to other anonymous practices in the network, with key features including antibacterial prescription and syndrome mapping.

Health Informatics research offers veterinary practitioners and their owners the chance to allow their animal's health data to be used for research, helping to fill the gap in companion animal surveillance and providing a new source of evidence to inform best clinical practice.

Key References

1.  Buckland EL, O'Neill D, Summers J, Mateus A, Church D, Redmond L, Brodbelt D. Characterisation of antimicrobial usage in cats and dogs attending UK primary care companion animal veterinary practices. Veterinary Record. 2016;179(19):489. DOI: 10.1136/vr.103830. Epub 2016 Aug 19.

2.  O'Neill DG, Gostelow R, Orme C, Church DB, Niessen SJ, Verheyen K, Brodbelt DC. Epidemiology of diabetes mellitus among 193,435 cats attending primary-care veterinary practices in England. Journal of Veterinary Internal Medicine. 2016;30(4):964–72. DOI: 10.1111/jvim.14365.

3.  Sánchez-Vizcaíno F, Singleton D, Jones PH, Heayns B, Wardeh M, Radford AD, Schmidt V, Dawson S, Noble PJ, Everitt S. Small animal disease surveillance: pruritus, and coagulase-positive staphylococci. Veterinary Record.2016;179(14):352–355. DOI: 10.1136/vr.i5322.

4.  Singleton DA, Sánchez-Vizcaínoa F, Dawson S, Jones PH, Noble PJ, Pinchbeck GL, Williams N, Radford AD. Patterns of antimicrobial agent prescription in a sentinel population of canine and feline veterinary practices in the United Kingdom. The Veterinary Journal. 2017;224:18–24. DOI: 10.1016/j.tvjl.2017.03.010.

5.  Tulloch JSP, McGinley L, Sánchez-Vizcaíno F, Medlock JM, Radford AD. The passive surveillance of ticks using companion animal electronic health records. Epidemiology and Infection. 2017;145(10):2020–29. DOI: 10.1017/S0950268817000826.