Artificial intelligence puts veterinary data at CVM community’s fingertips
Human medicine has long been able to use artificial intelligence (AI) to mine patient data to augment clinicians’ and researchers’ work. Now, thanks to an effort by the information technology team at the Cornell University College of Veterinary Medicine (CVM), the tools of AI and machine learning will soon be at the fingertips of the college’s faculty, staff and students.
“Right now, in the veterinary industry, much of the data is still siloed,” says Scott Ross, assistant director of application development and integration. “We’re trying to address that issue long term.”
Established as a goal of the CVM strategic plan, college faculty and administration pledged to improve the ability to analyze clinical, research and business data. “The college has a wealth of contemporary and historical clinical data that we have long wanted to use more effectively for research, education and practice,” says Lorin D. Warnick, D.V.M., Ph.D. '94, the Austin O. Hooey Dean of Veterinary Medicine. “This recent work done by the information technology team is a major achievement towards this goal.”
Striving for data-based decisions
The mission has been spearheaded by Dr. Meg Thompson, associate dean for hospital operations and director of the Cornell University Hospital for Animals (CUHA), encouraging technology at CVM to catch up with long-held promises. Thanks to Thompson’s strategic vision and leadership, CVM is poised to be the veterinary leader in world of data-driven AI platforms. Very few veterinary institutions have developed comprehensive, searchable databases for daily use in the clinic, classroom and lab.
“We’re trying to answer some really interesting questions,” says Ross. “We’d like to move the needle in veterinary medicine toward more evidence-based decision making. Thanks to Dr. Thompson, the college is beginning to realize the power of the data held in many of its applications.”
Thompson built strategic partnerships with industry leaders, including ezyVet, while simultaneously allowed the information technology team to concentrate on innovative solutions over operational concerns.
The data used for these applications includes everything from the 1.4 million clinical cases CUHA and Cornell University Veterinary Specialists have recorded, some going back to the early 1970s — to the 14.2 million diagnostic tests that the Animal Health Diagnostic Center (AHDC) has documented since 2000. They also include 90 terabytes of pathology slides that were digitized during the pandemic to allow veterinary pathologists to view tissue samples remotely. Beyond the veterinary medicine space, the project has also incorporated administrative data from human resources and accounting platforms.
The first step with these multi-million datasets was to do 'data positioning,' a technical term that means “massaging it to make it usable for people,” says Ross. After massaging this data, the information technology team, including software developers Steve Halasz and Daniel Sheehan, coded three apps to make them easily useable: Case Search, Case Experience and Cohort Builder. These three initial apps benefit each of the college’s main missions — care, education and research.
These modest beginnings are the start to a long-term data strategy in CVM.
Released in June 2020, this digital app allows faculty, staff and students to do a Google-like search of the millions of clinical cases recorded since the 1970s using a variety of keywords, including diseases, breeds and owner names — instantly pulling up results that show master problems, medications, labs, diagnosis and more.
Released in September 2021, this app provides a comprehensive dashboard of all clinical cases seen by any clinician or student at the hospital, allowing a per-person breakdown of species and breed they’ve treated, diseases they’ve treated, medications and procedures they’ve used and case timelines. This is particularly useful for students in their clinical rotations and specialty trainees, who can then view and track the breadth of their clinical experiences in one view. It enables both faculty and students to identify potential gaps in competencies and track progress and will aid in the college’s dedication to competency-based curriculum.
Slated for release in 2022, this app will make conducting clinical studies much easier. Cohort Builder identifies groups of patients for research projects using heterogeneous datasets, accurately identifying relevant patients and associated data, improving the quality of studies and research. For example, a clinician scientist who wants to study how successful a surgical technique is in a certain group of dogs would normally have to spend hours manually searching old cases that fit that criterion, record individual data fields in a spreadsheet and then analyze the outcomes of each case to arrive at an answer. Cohort Builder does that automatically, pulling all relevant cases, so that researchers can put together a large sample size for their analysis.
“For all clinical research that involves searching medical records, particularly retrospective cohort studies, this kind of technology is hugely helpful,” says Dr. Robert Goggs, associate professor of emergency and critical care. “We are always looking to maximize the number of patients we can include in our studies while also ensuring we get high quality, complete data. Using AI to mine the wealth of our collective medical records to help answer research questions is a huge time saver.”
These three data-mining developments are only the beginning of the information technology team's vision. Ross notes that they hope to mine human resources and administrative data for other types of analyses, and with other opportunities of growth on the horizon. As the team continues to build elegant applications that harness the wealth of information long stored at the college, it promises to make CVM’s efforts all that more impactful.
“We’re excited to put these tools in the hands of our faculty, staff and students to make their day-to-day lives easier,” says Ross.
Written by Lauren Cahoon Roberts