For every five appointments at Boston Children’s Hospital, one patient doesn’t show up.
Missed appointments are a common problem at health systems. And they’re a particularly attractive target for machine learning researchers, who can use patient datasets to get a handle on what’s causing patients to miss out on needed care. In new research published this month, a group of researchers at Boston Children’s crunched more than 160,000 hospital appointment records from almost 20,000 patients for clues. Their model found patients who had a history of no-shows were more likely to miss future appointments, as were patients with language barriers and those scheduled to see their provider on days with bad weather.