The percentage of radiology patients who did not show up for their appointments may sound insignificant: between 2.26 and 3.36 percent, based on a 16-year study of outpatient imaging appointments.1 However, when these patients miss an imaging appointment, the department loses money, time, and the ability to provide care, says Puneet Bhargava, MD, professor of radiology at the University of Washington in Seattle. Even though the overall percentage of no shows may seem relatively small, it’s still worth analyzing the no-show problem across a healthcare system. And recent studies show predictive models and personalized intervention can help decrease these rates and connect patients with the care they need.
Evaluating the Challenge
Bhargava explains that because the percentage of no shows is relatively small, there has not been a lot of focus on how to change that rate. However, the average doesn’t reveal the whole picture, according to Bhargava. It’s common to find a few modalities that have a much higher and alarming no-show rate, he says. He notes, “Screening studies such as mammography typically have higher no-show rates. Depending on the modality, this can be a much bigger problem in terms of uncaptured revenue. For instance, if you think of the expense of wasted radiotracers and the cost of PET-CT machines themselves, it can be a real issue to have those patients not show.”
In another study, Bhargava was part of a team that explored the financial burden of no shows on imaging.2 They concluded that at a typical academic medical center, the no shows for radiology could result in up to $1 million in lost revenue per year. For some modalities, such as radiography, it is easy to add patients to fill in slots when patients don’t show. But for certain areas like nuclear medicine, especially for PET-CT studies, there is likely less agility to fill last-minute open appointments — since tracers have to be ordered ahead of time and patient preparation is needed. And so, what results is uncaptured revenue when staff is being paid, equipment goes unused, but patients don’t appear. However, Bhargava says there is a much more important loss. “You absolutely want to provide care to a patient who is missing,” he adds. “You want to do everything in your power to make sure they show up and get the imaging they need.”
Creating Predictive Models
Bhargava was part of a team that created a predictive model to assess which patients are most likely to not show up for their imaging appointments.1 The model takes into account three different factors:
- Patient-related information, such as age, gender, income, and location
- Exam-related information, such as the type of exam, length of exam, and whether sedation is required
- Scheduling-related information, such as lead time, frequency of reminder, and format of reminder
The team found that those who were retired from work were much more likely to show up than those ages 35–50, who were more likely to have difficulty getting time off work or finding childcare. The less the lead time for scheduling an imaging appointment, the more likely they were to show up. No-shows rates were also lower when studies are performed after hours and over the weekend. Patients were also less likely to show up for screening — perhaps because it is seen as optional if you aren’t already sick, according to Bhargava.
You absolutely want to provide care to a patient who is missing. You want to do everything in your power to make sure they show up and get the imaging they need.
Dania Daye, MD, PhD, a radiology resident at Massachusetts General Hospital (MGH), was also part of a study of patient no shows in her department. Some of her team’s findings included higher no-show rates among underrepresented minorities, Medicare and Medicaid patients, and non-English speakers.3 Daye says this research got the department thinking about how to limit these disparities and provide equal care to everyone. “We wanted to do something to target these specific populations,” she says.
Personalizing the Approach
So what specific steps can radiologists take to decrease no shows? Well, for starters, McKinley Glover IV, MD, MHS, a radiologist who has worked with Daye at MGH on the aforementioned research projects, actually suggests that radiologists stop calling them no shows altogether. “The term ‘no show’ implies that responsibility solely lies with the patient and does not account for the role radiology departments’ systems and processes may play in creating barriers to receiving care,” he says. “Instead, we recommend the term ‘missed care opportunity,’ because radiologists and staff should be thoughtful about making targeted patient-centered changes that may improve access and utilization of imaging services.”
Bhargava agrees. He emphasizes that each department should first try to assess its own specific areas of high no shows, as well as likely patient factors. According to Bhargava, practices should be able to pull information about missed appointments from their EHR to help pinpoint where the rates are highest, which should be low-hanging fruit. Consider prioritizing a phone call from a scheduler for costlier imaging tests or for those patients with a previous history of no-show behavior, says Bhargava. He adds that robocalls, text messages, and email reminders can be customized and can help identify early if a patient is not planning to attend their appointment so that their slot can be filled by another patient.
According to Bhargava, if a patient has missed several previous imaging appointments, you can also decide to double book or schedule them for off hours. “Each department needs to come up with their own way to handle patients who have consistently missed appointments in the past,” he says. “Speak to your administrators and develop a consistent and firm policy.”
Additionally, says Daye, make specific interventions based on what isn’t working. Are you calling patients who work long hours and may not be able to pick up the phone? Try texting them instead. Many institutional systems also use automated e-mail reminders, so see if yours offers that option. Are you texting patients in their 80s, who may not be tech savvy? Pick up the phone and call them. “Optimize technology based on the individual,” Daye explains. This will take some additional time and resources, but Daye hopes these personalized approaches can help get patients to their appointments.
According to Bhargava, while radiology has made progress in understanding the impact of no shows and why they occur, there is more to be done. “The next step will be seeing how these new interventions work and tailoring them even more,” says Bhargava. “We need to make our approach as effective as possible so we can help the greatest number of patients.