Looking at patient history, schedules and demographics, we use machine learning to predict how likely a patient is to miss their scheduled appointment,
NASHVILLE, Tenn. (PRWEB) July 14, 2016
Intermedix announced Thursday the release of its patient no-show predicting capability as an added tool in its provider analytics solution.
This latest development is one of the ways that the company is responding to the increasing need for office-based providers to optimize their revenue.
“Providers’ revenue streams continue to decrease in today’s health care environment,” said Intermedix CEO Joel Portice. "This trend especially impacts small to midsize office-based practices. Our goal is to develop creative solutions for their challenges.”
Studies have shown that 5 - 10 percent of scheduled patients miss their appointments. At an average revenue of $228 per office-based physician visit, office-based providers experience significant revenue loss associated with these so called patient no-shows.
“Our new patient no-show predicting capability gives providers a powerful tool to remedy this loss of revenue,” continued Portice.
The no-show predicting capability is the first major development released by the company’s new analytics business unit.
“Looking at patient history, schedules and demographics, we use machine learning to predict how likely patients are to miss their scheduled appointments,” said Justin Schaper, who leads the analytics business unit at Intermedix.
This predictive capability assigns all patients a percentage score. The higher the percentage, the more likely a patient is to miss their appointment. Armed with this information, providers and practice administrators can make data-driven adjustments to their schedules.
“Providers now have the information they need to identify the best course of action for their practice,” explains Schaper. “Whether that means they increase the number of appointment reminders for patients who are less likely to show up or schedule multiple patients with high likelihood of not showing up during the same time slots.”
For Intermedix, the important thing is that providers can now make an informed decision based on reliable data.