Falls 75% Less Likely to Result in Major Injury With Nurse-Led, AI Predictive Care Model

PHILADELPHIA—BAYADA Home Health Care, a nonprofit home healthcare provider, announced new data suggesting that falls are 75% less likely to result in major injury when a BAYADA Home Health Aide is present. The finding comes from BAYADA’s Enhanced Quality of Care model that helps older adults stay safe and well at home using 40+ client datapoints and predictive AI technology to inform nurse-led care coordination.

Introduced nearly a year ago, the company said the care model now supports about 8,000 older adults nationwide who receive BAYADA’s private-pay personal care services.

Falls are the leading cause of injury among older adults, and when a fall results in major injury, the consequences compound quickly. One in four older adults report falling every year, and the average inpatient cost of a fall-related hospitalization is nearly $19,000. Such injuries can be followed by a recovery period and complications associated with a lasting loss of independence, even death.

Fear of falling can cause older adults to limit their activity and social engagement, accelerating the very decline they want to prevent. Reducing the severity of harm when falls occur is not only a clinical goal; it is central to preserving older adults’ independence and quality of life.

Since adopting this care model, BAYADA said it has observed a directional decline in falls with major injury—a significant drop of about one major injury per week and 58 major injuries per year among this older adult population.

BAYADA said its AI-predictive technology helps nurse clinical managers identify an individual’s high-risk periods—getting up in the morning, bathing or other routine moments where a fall has occurred before—and supports staffing those hours. The goal is not more care hours, but the right care hours.

“The measurable impact of homecare happens one intervention and one improved outcome at a time,” said Matthew Kroll, BAYADA practice president of personal care services. “This early trend tells us that when nurses and their care teams can see risk coming and act on it, our clients benefit. Falls are where we have the clearest data today, but this model is about anticipating risk more broadly—and intervening with the right care at the right time.”

BAYADA said it is also partnering with payers to develop a similar risk model for Medicaid clients, bringing this nurse-led, data-informed approach to a broader population.