A digital diagnosis and treatment tool for pets tackles vet shortage

The tool provides veterinarians with a quick and easy way to access reference information

Spotted: More than 23 million American households—almost one in every five—adopted a pet during the pandemic. However, pet ownership in the US faces a worrying threat: a shortage of veterinarians. This shortage could have a serious impact on animal health and welfare. The American Veterinary Medical Association (AVMA) is urging action to ensure that there are enough skilled practitioners to meet the needs of animal owners across the country. But what role can digitisation play? 

In the face of staff shortages, Finnish company GekkoVet hopes to improve the quality and speed of clinical decision-making by providing a digital tool that streamlines the process of diagnosis.

In order to help human vets come to a speedy diagnosis, the GekkoVet tool synthesises over 50,000 pages of clinical source material to provide a list of clinical symptoms. The vet then selects the relevant symptoms and the tool returns a list of possible diagnoses ranked according to probability. This approach makes it much easier for vets to access the vast amounts of reference information they rely on, saving them precious time without undermining their clinical judgement, knowledge, and expertise.

“In the face of severe staff shortages that aren’t going anywhere soon our industry has no choice but to evolve to survive,” explains Arbor Pointe Veterinary Hospital owner and veterinarian Dr. Mike Petty. “For too long we’ve relied on Google and stacks of books for our reference needs. Everything else is accessible from a few taps on a cell phone—except clinical (decision making) tools.”

GekkoVet recently appeared as a showcase finalist at the Animal Health, Nutrition and Technology Innovation summit in Boston.

Springwise has recently spotted innovative approaches to streamlining the diagnosis of human conditions. These include deep AI imaging diagnostics that help doctors prioritise patient care, the use of whole genome sequencing to diagnose rare diseases, and deep learning image analysis for breast cancer diagnosis.