This FQHC slashed its patient no-show rate with AI in 3 months

Urban Health Plan tested eClinicalWorks' healow prediction algorithm and increased its show rate for the patients most likely to miss their appointments by 154% with targeted interventions.

The New York City-based Urban Health Plan used artificial intelligence to improve operational efficiency and patient care and got a handle on its annually high patient no-show rates with cost-effective patient interventions.

Higher-than-average missed appointments

No-shows are due to multiple factors, including social determinants of health like transportation. 

But they are also a long-standing challenge to healthcare organizations that can affect the patient's care quality, increase healthcare organization costs and present unnecessary reductions in overall patient access to healthcare appointments.

In March, Urban Health Plan had 42,000 health visits – the highest in its history, according to a presentation at an eClinicalWorks health summit in Boston last week. 

"We had a multifaceted approach to just addressing patient access and engagement overall," Alison Connelly-Flores, chief medical information officer of Urban Health Plan, told Healthcare IT News. 

That achievement is significant because annually, UHP experiences a high number of missed appointments and appointments for patients waiting are sometimes "booked out way too far." Providers are typically overbooked to accommodate for no-shows, said Connelly-Flores.

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