Evidence in Practice – A Pilot Study Leveraging Companion Animal and Equine Health Data from Primary Care Veterinary Clinics in New Zealand

Abstract

Veterinary practitioners have extensive knowledge of animal health from their day-to-day observations of clinical patients. There have been several recent initiatives to capture these data from electronic medical records for use in national surveillance systems and clinical research. In response, an approach to surveillance has been evolving that leverages existing computerized veterinary practice management systems to capture animal health data recorded by veterinarians. Work in the United Kingdom within the VetCompass program utilizes routinely recorded clinical data with the addition of further standardized fields. The current study describes a prototype system that was developed based on this approach. In a 4-week pilot study in New Zealand, clinical data on presentation reasons and diagnoses from a total of 344 patient consults were extracted from two veterinary clinics into a dedicated database and analyzed at the population level. New Zealand companion animal and equine veterinary practitioners were engaged to test the feasibility of this national practice-based health information and data system. Strategies to ensure continued engagement and submission of quality data by participating veterinarians were identified, as were important considerations for transitioning the pilot program to a sustainable large-scale and multi-species surveillance system that has the capacity to securely manage big data. The results further emphasized the need for a high degree of usability and smart interface design to make such a system work effectively in practice. The geospatial integration of data from multiple clinical practices into a common operating picture can be used to establish the baseline incidence of disease in New Zealand companion animal and equine populations, detect unusual trends that may indicate an emerging disease threat or welfare issue, improve the management of endemic and exotic infectious diseases, and support research activities. This pilot project is an important step toward developing a national surveillance system for companion animals and equines that moves beyond emerging infectious disease detection to provide important animal health information that can be used by a wide range of stakeholder groups, including participating veterinary practices.

Evaluation of a novel syndromic surveillance system for the detection of the 2007 melamine-related nephrotoxicosis foodborne outbreak in dogs and cats in the United States

“…This and several other large-scale foodborne illness outbreaks in dogs and cats during the last decade signaled the need for a nationwide companion animal surveillance program (Bischoff & Rumbeiha, 2018;Burns, 2007). However, compared to advancements in computational technology and data science, the development of companion animal surveillance seems to be lagging (McGreevy et al, 2017;Muellner et al, 2016;Hale et al, 2019). Lack of centralized veterinary medical databases is probably one of the largest challenges hampering its progress (O'Neill et al, 2014).…”

Epidemiology and clinical outcomes of feline immunodeficiency virus and feline leukaemia virus in client-owned cats in New Zealand

“…New initiatives are currently underway in New Zealand to improve data capture from electronic medical records that will hopefully make these type of monitoring studies easier in the future. 46 , 47…”

Peer Review #1 of "Evaluation of a novel syndromic surveillance system for the detection of the 2007 melamine-related nephrotoxicosis foodborne outbreak in dogs and cats in the United States (v0.1)"

“…This and several other large-scale foodborne illness outbreaks in dogs and cats during the last decade signaled the need for a nationwide companion animal surveillance program [8,9]. However, compared to advancements in computational technology and data science, the development of companion animal surveillance seems to be lagging [10][11][12]. Lack of centralized veterinary medical databases is probably one of the largest challenges hampering its progress [13].…”