The Impact of Big Data in Veterinary Medicine

Banfield Pet Hospital has released their annual VET Report. Read how Big Data is changing the landscape of veterinary medicine.

Thanks to digital technologies and sophisticated analytical techniques, we can collect and process larger amounts of diverse data faster than ever before. Coined as “Big Data,” these large, complex, and rapidly accumulating datasets are transforming how industries operate. In veterinary medicine, this includes everything from identifying high-risk populations and modeling epidemiological processes, to detecting emerging threats and informing our understanding of health and disease in both pets and people.

At Banfield, we have access to vast amounts of data through our proprietary data and electronic medical records system, which houses insights from more than 9.5 million visits and 3.5 million pets seen per year with an average of about 70 data points recorded per visit. This information enables us to study patient outcomes and monitor trends in pet health to improve quality in veterinary medicine.

We are dedicated to sharing our findings with the broader profession, and since 2017 we have published a series of Veterinary Emerging Topics (VET)™ Reports on subjects ranging from osteoarthritis and obesity, to quality, to safety improvement. This year’s 2023 VET Report is all about how we use Big Data to create impact. The full report can be found on Banfield Exchange, and below are a few examples from the report of how we use this data to improve the quality of veterinary medicine and advance pet health, as well as actions that you can take in your own practice.

Reducing Anesthesia-Related Mortality

Although it is rare, even small reductions in anesthesia-related mortality can have enormous significance for patients, clients, and veterinary teams.

. Big Data: We collected peer-reviewed literature, professional guidelines, and position statements and scrutinized internal data from medical records and safety reports to identify the systemic and local risks associated with anesthesia. We then developed and implemented medical quality standards (MQS) to mitigate them.

. Big impact: Six months after the implementation of MQS, mortality rates decreased, preventing at least one additional death per 10,000 procedures. We have seen ongoing and sustained reductions in these rates and, to date, have recorded the lowest mortality rates ever measured. Even with this positive impact, we will continue to ‘chase zero’ and continuously utilize data to make improvements where possible.

Identifying Pets at Risk of Renal Disease

Research has found chronic kidney disease (CKD) is the leading cause of mortality in cats >5 years of age and generally has an even worse prognosis in dogs.

. Big Data: Our medical record data was used to build models for predicting the risk of developing CKD in cats and in dogs by applying advanced machine learning methods to data collected during routine veterinary practice visits.

. Big impact: Machine learning applied to Big Data can support veterinary decision-making by improving early detection of CKD, providing a greater opportunity for intervention, which can result in a better quality of life and longer survival. Because they rely on data already collected during routine veterinary visits, the models could be readily implemented in hospital practice or diagnostic laboratory software, such as RenalTech, to directly support veterinarians making clinical decisions.

“By analyzing medical data from Banfield patient visits over two decades, Mars Petcare scientists created the RenalTech tool using artificial intelligence to predict whether a cat will develop CKD up to two years before traditional clinical diagnosis,” said Nefertiti Greene, President, Mars Science & Diagnostics. “Available to veterinarians that use Antech’s reference laboratories in the U.S., RenalTech can predict CKD with greater than 95 percent accuracy. This tool is the first of many predictive diagnostics in the pipeline from Mars Petcare as we continue to invest in enabling more personalized healthcare for pets.”

Recognizing Risk Factors for Vaccine-Associated Adverse Events

Vaccine-associated adverse events (VAAEs) are rare, but clients who are concerned about them may decline or delay their pets’ vaccinations, leaving them vulnerable to preventable infectious diseases.

. Big Data: We partnered with Purdue University’s College of Veterinary Medicine to complete what we believe to be the largest VAAE study of dogs to date. Incidence in this analysis was 18.4 VAAEs per 10,000 dogs vaccinated, less than half what it was more than 15 years ago. Smaller dogs, particular breeds of dogs, and those receiving multiple vaccines in the same visit were more likely to experience a VAAE.

. Big impact: The large drop in incidence of VAAEs suggests that newer vaccines are safer, which likely speaks to the diligence and responsibility of vaccine manufacturers. Additional investigations into these incidences are planned, including partnering with Wisdom Panel to look into how genetic factors may influence the risk of VAAE, studies on feline VAAEs, and more.

Realizing the full potential of Big Data to improve disease detection, delivery of care, and sustainability in veterinary medicine will require consistent, collaborative efforts to collect the necessary information. For example, Associates from Banfield and Mars Veterinary Health, along with colleagues at Mars Petcare, recently teamed up to develop the biggest dataset in veterinary medicine yet. The MARS PETCARE BIOBANKTM will include data collected from 10,000 dogs and 10,000 cats over a 10-year period with the goal of driving breakthroughs in scientific knowledge for the future of veterinary medicine.

Improvements in pet health will only be accelerated when we collaborate across the profession. Talk with your hospital team about how you might be able to play a part, whether that’s expanding your use of electronic medical records and other digital technologies, conducting data and analytics work at your hospital, or contributing to one of the large data aggregation efforts in progress. In each case, you’ll be improving the quality of veterinary medicine in support of advancing the future of pet health.