Ai Adoption Fast-tracks Home Health Providers’ Path To Value-based Care

Artificial intelligence (AI) shows promise to improve patient outcomes, simplify operations and enhance patient outcomes while reducing costs, but only a fraction of home health care providers have adopted AI technology.

Those that have adopted AI technology have found that its promise extends past streamlining operations – it has become a vital rung on the ladder toward value-based care.

Value-based reimbursement models have been gradually incorporated into the U.S. health care system to improve patient outcomes and lower costs. In 2022, about 24.5% of U.S. health care payments were directed through risk-based advanced payment models, up from 20% in 2021, according to a survey of payers published by the Health Care Payment Learning & Action Network. 

As value-based care models require careful data tracking, AI has proved an essential tool for providers in need of an efficient way to track and analyze key metrics.

“The only way you can measure is by collecting data and having metrics to go against,” Naomi Goldapple, senior vice president of data and intelligence at AlayaCare, told HHCN. “One of the things that is hard to do is to collect all of the data that goes into measuring the quality of care, and for a human being to crunch that. How do you actually use that to provide decision support and help improve metrics? So, what AI can do is grab and aggregate all that data and leverage notes and narratives using predictive algorithms to identify those at risk of an adverse event.”

AlayaCare serves more than 500 home-based care agencies across the U.S., Canada and Australia.

Goldapple stated that the data can then be used in daily decision-making and resource allocation to ensure that high-risk patients are prioritized and steps are taken to mitigate risks. These mitigations are then measured to determine what led to patient improvements.

AI can examine datasets, including clinical history, lifestyle choices and social determinants of health, to identify patients at high risk for adverse events like hospitalization or disease progression. This enables home health agencies to allocate resources more efficiently and take proactive steps before a patient’s condition deteriorates, and can lead to fewer hospital readmissions and emergency visits, according to Goldapple.

“I see leveraging AI to gather all data and identify high-risk [home health] patients earlier,” Casey Hite, CEO of Aeroflow Health, told Home Health Care News. “Using predictive algorithms to not only find these patients but also reduce hospital admissions. We must keep data private just as we do without AI, but ultimately, AI can compile vast amounts of data, analyze it and extract insights much faster than humans — and so we should leverage it rather than fear it.”

Ashville, North Carolina-based Aeroflow is a durable medical equipment provider offering maternal, continence care, diabetes and sleep products. The company is expanding its use of AI to improve its sleep apnea and diabetes patient care tools by integrating AI-powered solutions for predicting patient adherence to therapy and providing personalized coaching and support. It offers AI-driven digital coaching and insights to home-based care providers and other health providers who use its equipment.

Hite said that identifying these patients earlier and more cost-effectively helps reduce health care costs and increases efficiency.

The tools to make a difference

Ongoing development of predictive models, AI-powered virtual assistants and data-sharing platforms will likely make home health care even more accessible, efficient and patient-focused, supporting the main goals of value-based care.

Providers have begun to turn to an array of AI tools, from wearables to documentation aids.

AI-powered remote patient monitoring systems, using wearables and sensors, continuously track patients’ vital signs and activity levels in real time from the comfort of their homes. Algorithms identify subtle changes or anomalies that could indicate a coming health problem, like an upcoming heart failure or respiratory issue, and alert care teams for quick intervention.

AI incorporates data from various sources, such as these, to develop a comprehensive view of a patient’s health and social environment, allowing for the customization of care plans based on individual needs and risk factors. The technology automates personalized outreach to patients, medication reminders, and wellness education through chatbots and virtual assistants, which enhances patient engagement and adherence to treatment plans, according to virtual health solutions provider, HealthArc

These AI-powered monitoring platforms allow for customized treatment approaches at scale without extra costs per patient, making personalized care both clinically effective and economically sustainable, according to researchers at Cedars Sinai Medical Center in Los Angeles.

Further, AI also automates time-consuming administrative tasks, including documentation, care plan creation, scheduling and claims processing. Automated, real-time documentation and note-taking free up caregivers to spend more time on direct patient care while also improving the accuracy of patient records and speeding up reimbursement cycles. It may also help with staff retention, as 82% of home health clinicians said that if a home health agency offered an AI tool that significantly reduced documentation time, it would make them more likely to join or stay with that organization, according to a 2025 survey conducted by WellSky. 

For example, Goldapple said AI can help compile caregiver notes and feed them into a dashboard that a clinical supervisor can quickly view and use to ensure patients are properly cared for and nothing is overlooked.

These tools can also enhance the patient experience through ambient listening. With ambient listening devices, caregivers can have face-to-face conversations with patients instead of being focused solely on their documentation.

“With AI, providers can spend more one-on-one time looking into the patient’s eyes and having more meaningful interactions, knowing that the data isn’t slipping away but being captured and possibly leading to downstream tasks,” Goldapple explained.

AI tools integrate with electronic health records to give clinicians data-driven insights and evidence-based recommendations at the point of care. This helps care teams make quicker, more accurate decisions, spot potential care gaps and streamline workflows, resulting in higher job satisfaction and improved quality of care.

The technology is advancing, and there are possibilities that workflows can be integrated into EHRs to alert caregivers and physicians in advance of symptoms to monitor before the patient even visits the office, according to Goldapple.

“It is even possible to reach out to the patient to understand how they are feeling or if there is anything they want to be sure to discuss during their visit so their concerns aren’t forgotten,” she noted. “The care plan could even be updated [almost immediately] if something has changed. There’s that conversation flow in a natural language way that can improve the relationship.”

An analysis by Gartner Research provides a framework for evaluating AI applications, considering both technical feasibility and their potential to generate value. 

The most promising applications combine high feasibility with meaningful clinical benefits. Automation of clinical documentation shows strong potential, as AI systems effectively convert medical conversations into structured records while requiring minimal workflow adjustments. Predictive analysis, augmentation and improvements in patient care navigation also offer high-value, practical solutions that can address existing technical and regulatory hurdles.

As AI technology matures and integration challenges are solved, its role in home health will continue to expand, according to Gartner.

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