How data can help reduce the number of missed appointments at veterinary practices
Editor’s note: This is the sixth installment in an ongoing series of articles on the topic of data-driven decisions (and helping your accounts make them). To view prior articles, please check past issues and archives. This and other articles in this series introduce ideas that can be used by industry reps who advise and support busy veterinary practices in their efforts to achieve greater growth and profitability.
Industry reps can learn a lot about their accounts by asking each of them a simple question: “In one sentence, how would you describe what you do at your practice every day?”
Although many of the answers will likely touch on similar things, the focus of each response may contain some interesting signals regarding the way people think about their businesses and their work. For example, some practice owners may say they heal animals, and others might respond by listing their daily tasks.
This question doesn’t have any wrong answers, of course, but the responses can help industry sales reps see through the eyes of the people in their accounts. When looking through those eyes, reps will generally find that most people don’t think of veterinary practices as complex systems involving many participants, activities, and dependencies.
Identifying growth opportunities with data
People who do take a systems-based view of their practice and their work can see how all the players and processes work together and influence each other, even when connections may not be obvious to people who think of their work as a set of discrete tasks. And when systems are understood properly, we can see the terrible second-order effects of irregularities, which can extend far beyond the initial problem they cause.
One particularly insidious (and frustratingly common) issue facing veterinary practices is the problem of clients missing their appointments.
A few years ago, a group of practices owned by a prominent veterinarian found through data analysis that they had room to improve the rate at which clients were missing appointments. Their analysis quickly turned up some easily quantified information. For example, more than 10 percent of their appointments on the calendar each day resulted in no-shows, only a small portion of those no-shows were proactively rescheduling, and many of those no-shows were with clients who had actually created the appointment they missed within 36 minutes of the appointment time.
But the group didn’t stop the analysis there; they wanted to understand the more-difficult-to-quantify costs associated with no-shows. So, they generated those data by doing customer interviews, staff interviews, and activity-tracking observations.
What they found by interviewing staff members included important insights, specific to their group, about the hidden (but very real) costs of no-shows like overstaffing, inefficient efforts trying to reschedule, worse health outcomes for patients, and more. In other words, the group discovered that no-shows were much more expensive than just the lost revenue they would’ve generated had the appointment been kept.
Data analysis informs the solution development
Armed with an understanding of the real size of the no-show problem, the group was well-prepared (and very motivated) to develop effective solutions. Knowing that many of the no-shows happened even though clients had already confirmed the appointment a few days before, or even made the appointment earlier that same day, led the group to experiment with sending an additional automated text message reminder just two hours before the appointment.
Importantly, these text message reminders were personalized with the signature of the doctor whom the clients were coming to see. Even though these text messages were automated, the doctor appeared to be personally looking forward to seeing the client and patient (and counting on them not to miss the appointment).
The results were exciting. In the nine months that followed, missed appointments dropped 17.9 percent. The group calculated that this resulted in $59,000 of additional revenue, as well as lowered the other real-but-more-difficult-quantify costs of dealing with no-shows.
Veterinary practices willing to analyze the data they have, and generate the necessary data they don’t have, can often find it surprisingly easy to implement changes that lead to meaningful improvements in health outcomes for their patients and financial outcomes for themselves. Well understood problems can be attacked by well considered solutions.
Proactive industry sales reps can help their accounts know what areas of the practice operations to study, what data to analyze, and how to develop solutions that lead to practice growth.
IDEAS IN BRIEF:
- Data analysis can highlight some surprisingly simple ways for veterinary practices to make surprisingly large improvements in their practices.
- One example is reducing missed appointments or “no-shows,” which have real costs, including some that aren’t obvious.
- Reviewing data on its no-shows will help a practice see the scale of the problem (how much it happens) and the causes of the problem (why and with whom it happens). Then, the practice can develop appropriate solutions, which can lead to meaningful revenue growth.
ALLYDVM aspires to be the veterinarian’s ultimate ally. The company provides data-driven software and advisory services to sophisticated veterinary practices throughout the country. ALLYDVM works with PhD-level data scientists and counts a number of past presidents of both AAHA and the AVMA as customers. Jason Wernli – Founder and COO; Scott Harper – CEO; firstname.lastname@example.org; 855-255-9386 (855-ALLY-DVM)