Karen E. Felsted
CPA, MS, DVM, CVPM, CVA
Take Charge columnist Dr. Karen E. Felsted is the founder of PantheraT Veterinary Management Consulting. She spent three years as CEO of the National Commission on Veterinary Economic Issues.Read Articles Written by Karen E. Felsted
Veterinarians understand the benefits of radiology, but its value depends on the accurate interpretation of images, which is often harder to accomplish compared with other diagnostic tools, such as laboratory testing. Enter radiographic interpretation using artificial intelligence, a relatively new option in veterinary medicine but one that many practices have embraced as a welcome addition to their reading of images.
AI shouldn’t be thought of as a replacement for a veterinarian’s skills and knowledge, regardless of whether the doctor is a general practitioner or specialist (particularly a board-certified radiologist). Instead, it’s an ancillary tool designed to improve patient care, the client experience and a veterinary practice’s efficiency.
The most important benefit centers, of course, on the quality of care. Using an AI radiology tool puts another set of eyes on an image and might confirm the practice team’s original findings or identify additional results. Either way, the team’s confidence in the reading improves, and support for the diagnosis and pet owner recommendations is strengthened. This is particularly helpful for recent DVM graduates and those with less radiographic interpretation experience. AI also can reduce the need for a more senior veterinarian to be involved in many interpretations.
Depending on the AI provider selected, quick turnaround of the reports (often within minutes) and around-the-clock availability elevate client service. In addition, providing the pet owner with a copy of the report can emphasize the importance and value of the diagnostic test.
Passing the cost of AI readings onto the client, most commonly with a markup, improves a practice’s revenue and profits. Radiology equipment costs the same whether used once a week or 50 times, so anything that increases its usage reduces the per-image cost.
One of the best things about implementing AI is the general ease and speed. But how do you go about it? Here are six steps.
1. Select an AI Radiology Provider
One of the first things you’ll investigate is the technology, but that’s far from the only consideration. See “Additional Factors” below.
2. Begin the Integration
Little to no change will occur when you take radiographs, but you’ll need to determine:
- How to upload radiographs to the AI provider. Often, it’s automatic.
- How your doctors will receive an AI report and when they’ll discuss the findings with clients. At some practices, the veterinarian prefers getting reports within minutes of taking the X-rays and then updating clients before they leave the building. At others, the doctor has an initial conversation with the client based on the first image reads and then reviews the AI report later in the day before sharing it with the pet owner by phone or electronically.
- How to inform clients about the AI service. For example, some practices say it’s another type of review and is treated as a benefit. Other hospitals might share the findings without mentioning AI.
3. Train the Team
Team members should know their roles and responsibilities when utilizing the technology. Ask yourself:
- Who will upload images to the AI platform if it can’t be done automatically?
- How will doctors retrieve the AI results before determining a diagnosis and treatment plan?
- How will AI findings be shown in the pet’s medical record? Will a doctor or someone else handle the task?
- Who will update radiographic service descriptions and prices in the practice information management system?
- Who will educate team members about how AI technology works in veterinary radiology and why it’s useful?
4. Price the Service
- Will the fee be separated, or will the cost (plus a markup) be reflected in the total price of the radiographs?
- How much of a markup? It can’t be so high that it discourages clients from accepting the diagnostic recommendation.
5. Create, Review and Update Your Radiologic Standards
Any medical protocol is a written guideline stating what the practice thinks is the best medicine in various situations. It doesn’t have to be followed if a client declines the recommendation or a doctor doesn’t think the protocol is warranted. Radiology protocols usually cover:
- The types of cases in which the medical team recommends radiographs.
- The types and number of images to be taken.
- Any related anesthesia recommendations.
6. Measure the Successes or Need for Improvement
Key metrics include:
- Radiology revenue as a percentage of total gross revenue.
- The number and percentage of clients who accept an AI X-ray recommendation.
- The number and percentage of pets who have X-rays done before and after the implementation of AI technology.
- The email open rate if AI reports are sent to the client.
- Client satisfaction.
- Doctor satisfaction with the use of AI and the provider.
There’s no question that some of the challenges veterinarians face in interpreting radiographs can be addressed through the increased availability and use of AI. Fortunately, the implementation doesn’t have to be complicated or expensive, and all parties will benefit.
When selecting a radiology AI provider, consider:
- How the AI algorithm was developed and its accuracy.
- The process for the ongoing revision and upgrade of the AI algorithm.
- The range of body areas and clinical problems covered by the assessment.
- The ease of integrating AI into the workflow and uploading images.
- The need for additional equipment, if any.
- The turnaround time for reports.
- The days and hours of report service availability.
- The ease of retrieving and reviewing reports.
- The quality of the reports.
- The AI provider’s technical support.
- The cost.