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Advancing One Health Datasets Workshop

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Objectives:

Review the current state of veterinary medical EHRs and the ability to aggregate and analyze large datasets from multiple organizations and clinics.
Review analytical techniques as well as research efforts into veterinary informatics with a focus on applications relevant to human and animal medicine.
Provide references and context for these resources so that researchers can identify resources of interest and translational opportunities to advance the field.

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Key points:

Approximately 500 million clinical records for dogs and cats are generated each year in the US

Mostly free text – systems designed for efficient charging

Practice Information Management Systems (PIMS) verses EMRs

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Key points:

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Key points:

No insurance incentive

and no workforce….

Lots of siloed data

Need incentive:

Human side due to translational applications
Impactful examples…

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Key points:

Diverse use cases: Biosurveillance

zoonotic disease
antibiotic resistance
disease outbreak prediction
clinical health
extended outbreak detection
disease outcome prediction
environmental health effects
rare diseases

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A.1 Veterinary Databases (as of Sept 2019)

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A.1 Veterinary Databases (as of Sept 2019)

>50,000

~2,500

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A.2 Publicly or Governmentally Funded Resources

Veterinary Medical Databases (VMDB)
The Veterinary Companion Animal Surveillance System (VetCompass)
The Small Animal Veterinary Surveillance Network (SAVSNET)
Tissue Biobanking Resources

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A.3 Private Sources

The Veterinary Information Network (VIN)
Pet Insurance Data
Pet Toxicology Resources
Veterinary Pharmacies

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A.4 Governmental Organizations

Center for Disease Control and Prevention (CDC)
United States Department of Agriculture (USDA)
Food and Drug Administration

A.5 Other Organizations

COHA

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Discussion:

Current limitations in the field of veterinary informatics include:

limited sources of training data for developing machine learning and artificial intelligence algorithms

siloed data between academic institutions, corporate institutions, and many small private practices

inconsistent data formats that make many integration problems difficult

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Discussion:

Despite limitations, there have been significant advancements in the field and continued development of a few, key, large data resources that are available for interested clinicians and researchers.

These real-world use cases and applications show current and significant future potential as veterinary informatics grows.

Veterinary informatics can forge new possibilities within veterinary medicine and between veterinary medicine, human medicine, and One Health initiatives.

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