Mobile app uses analytics to predict hospital readmissions

A mobile application that uses analytics to predict hospital readmissions and allows patients to more easily communicate with providers has the potential save the healthcare industry billions of dollars, its developers say.

Researchers at Binghamton University in New York created the app, the Post Discharge Treatment and Readmissions Predictor or PdtRp, which calculates a patient’s probability for readmission by mining historical records and comparing those to present-day status. The Centers for Medicare & Medicaid Services uses 30-day readmissions rates as a means to measure care quality, and to penalize poor-performing hospitals, if necessary.

“I don’t see anything similar to it on the market,” said graduate student Amirhosein Gholami, who helped design the app, according to an announcement. “If it can help to prevent even just 10 percent of patients from being rehospitalized, it’s big money.”

Patients can use the app to correspond with or send information to their healthcare providers directly, and also can send emergency requests to providers. In addition, patients can view their own readmissions reports. Healthcare miscommunications contribute to a quarter of preventable readmissions, according to research published earlier this year in JAMA Internal Medicine.

What’s more, health payers also can use the tool to send requests or alerts to patients’ providers, and can view patients' readmissions history.

The researchers are contemplating the addition of other features, including a medication scheduler and tracker that would be connected to a home medicine dispenser. They also want to make the Android-based tool available for iOS users.

To learn more:
- here’s the announcement