Home-based care provider Bayada is leveraging AI-enabled clinical decision-support tools to identify patients at elevated risk sooner, helping care teams intervene before conditions worsen or lead to hospitalization.
Rather than requiring clinicians to manually review notes across a patient’s record, the tools synthesize electronic medical record data and clinical documentation to flag risk signals denoting which patients need faster follow-up or changes to their care plan.
“Instead of reactive, we are more proactive,” Amy Hirsch, the divisional director of clinical practice and support for Bayada’s hospice team, said during a Thursday webinar featuring executives from Bayada and Mosai. Pennsauken Township, New Jersey-based Bayada provides home health, personal care, pediatric home health and other services from over 370 locations across five countries.
Nashville, Tennessee-based Mosai was formed through the merger of Forcura and Medalogix in 2025. The company provides software for home-based care providers and their partners, with offerings including predictive analytics, workflow automation and secure communication.
Hirsch described how technological advancements synthesize a patient’s health markers quicker than in prior years.
“In the past, you didn’t have the dashboard,” Hirsch said. “You didn’t have the technology or the AI as a tool to help you make judgments. As a clinician, you’re doing note by note, and then someone would have to read all that information and go, ‘Oh wait, Amy’s declining.’ … So definitely quicker decision making for better outcomes for our patients.”
Clinicians often make these prompt judgments within limited resource environments, said Bayada president Justin Searle. Under the constraints, providers must figure out how to triage and put resources toward the most vulnerable clients and pressing issues.
Bayada providers use Mosai Pulse, a real-time intelligence platform for clinicians aimed at preventing hospitalizations. According to Searle, the tool has eased Bayada’s documentation burdens and limitations caused by staffing shortages to provide more effective care.
Searle emphasized that AI-enabled technology is meant as a tool facilitating clinical care, not a stand-in for it.
“We’re thinking about AI, certainly not in terms of a replacement perspective, but to help enable them to be working at top of title, top of license,” he said.
Searle shared a case study in which the AI-enabled tools improved outcomes for one patient: a 75-year-old client with kidney disease and heart failure. The Pulse dashboard adjusted her to the high-risk category after she gained 13 pounds in a short timeframe.
Bayada clinicians saw the weight gain, and then a cardiologist adjusted in a timely manner. Between the coordinated care, cardiologist intervention, ensuring the patient could track her own weight and frequent care phone check-ins, the patient’s weight “materially subsided,” said Searle. Pulse then moved her out of the high-risk category within the dashboard.
Pulse’s flag allowed the patient to get the care she needed and avoid the “stale, sterile hospital bed where nobody wants to be,” Searle said.
“That’s a hospitalization saved,” he added. “That’s more time. That’s more moments for her in her home.”