Syndromic surveillance in companion animals utilizing electronic medical records data: development and proof of concept.

Philip H Kass,Hsin-Yi Weng,Elizabeth M Lund,Max H Sydow,Amy Hille,Peter J Markwell,Mark A.L Gaona

doi:10.7717/peerj.1940

Abstract

In an effort to recognize and address communicable and point-source epidemics in dog and cat populations, this project created a near real-time syndromic surveillance system devoted to companion animal health in the United States. With over 150 million owned pets in the US, the development of such a system is timely in light of previous epidemics due to various causes that were only recognized in retrospect. The goal of this study was to develop epidemiologic and statistical methods for veterinary hospital-based surveillance, and to demonstrate its efficacy by detection of simulated foodborne outbreaks using a database of over 700 hospitals. Data transfer protocols were established via a secure file transfer protocol site, and a data repository was constructed predominantly utilizing open-source software. The daily proportion of patients with a given clinical or laboratory finding was contrasted with an equivalent average proportion from a historical comparison period, allowing construction of the proportionate diagnostic outcome ratio and its confidence interval for recognizing aberrant heath events. A five-tiered alert system was used to facilitate daily assessment of almost 2,000 statistical analyses. Two simulated outbreak scenarios were created by independent experts, blinded to study investigators, and embedded in the 2010 medical records. Both outbreaks were detected almost immediately by the alert system, accurately detecting species affected using relevant clinical and laboratory findings, and ages involved. Besides demonstrating proof-in-concept of using veterinary hospital databases to detect aberrant events in space and time, this research can be extended to conducting post-detection etiologic investigations utilizing exposure information in the medical record.

Highlights

Surveillance provides the key linkage between naturally occurring disease or syndrome occurrence and its real-time recognition (Henning, 2004; May, Chretien & Pavlin, 2009; Wójcik et al, 2014)
This study reports on the development of analytic and interpretive protocols based on the proportionate diagnostic outcome ratio (PDOR), and their implementation to evaluate surveillance instrumental performance using two simulated outbreaks
A workshop was convened that included external academic experts in epidemiology, nutrition, toxicology, infectious diseases, internal medicine, food safety, and clinical pathology in order to establish a set of syndromes optimal for conducting foodborne disease surveillance in companion animals; none were involved in the design of this research or in the preparation of this manuscript

Summary

Introduction

Surveillance provides the key linkage between naturally occurring disease or syndrome occurrence and its real-time recognition (Henning, 2004; May, Chretien & Pavlin, 2009; Wójcik et al, 2014). The last decade has seen an increase in implementation of surveillance systems both in human populations (primarily to detect pandemic infectious disease (e.g., H1N1 influenza, SARS) and bioterrorism events Drewe et al, 2012; Milinovich et al, 2014) and animal populations (Dórea, Sanchez & Revie, 2011) These systems alone do not have immediate applicability to companion animal populations, there has been interest in the United Kingdom and United States in monitoring zoonotic disease in such populations (Day et al, 2012; Glickman et al, 2006; Halliday et al, 2007; Maciejewski et al, 2007; Shaffer et al, 2007).

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