Analytics helps spot risk for missed appointments

Tuesday, November 29 | 3:30 p.m.-3:40 p.m. | SSJ13-04 | Room S402AB
In this session, researchers will describe how predictive analytics can help identify patients who may be at higher risk for missing their radiology appointment.

Healthcare disparities are present in medicine across many socioeconomic and demographic groups, and radiology is no exception, according to Dr. Efren Flores of Massachusetts General Hospital (MGH). Hoping to do something about it, an MGH team launched the Patient Engagement for Equity in Radiology (PEER) project. The goal of PEER is to develop an informatics-driven, collaborative platform that will increase patient engagement in the healthcare system and facilitate equitable healthcare delivery.

"This will allow us to provide compassionate care to our patients by understanding our patients' needs and develop effective programs to provide additional assistance to those patients who may need it," Flores said.

The predictive analytics model analyzes socioeconomic, demographic, and medical characteristics to identify factors that are strongly associated with missed radiology appointments or, as MGH now calls them, missed care opportunities (MCOs). Rather than call them no-shows, the researchers use the new term to account for the responsibility of healthcare providers in patient engagement, Flores said.

"Our MCO predictive model has identified 14 different factors that place a patient at risk for an MCO event or low engagement, including language, insurance type, and education level, among others," Flores told "This model has guided us into developing current and future programs, such as coordinated care with multiple appointments, facilitating transportation, and text messaging reminders in a preferred language."

Learn more about the model and the institution's programs for addressing missed care opportunities by attending this Tuesday afternoon talk.

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