It’s coming home

American patients often struggle to access the care they need due to barriers such as lack of proximity to care providers or difficulty securing timely appointments.

In 2023, more than 40% of Americans experienced longer than reasonable waits for healthcare, with 26% of those surveyed waiting more than two months to see a healthcare provider.

These barriers to care often lead to patient frustration and foregoing care altogether, as nearly half of those who experienced longer than reasonable wait times gave up and did not receive care.

These access gaps and delays are expected to worsen. The shortfall of physician demand against supply in the US is projected to grow, attributable partly to ageing US patient and physician populations.

Use of artificial intelligence allows for a broader reach and application of home-based care, which is projected to continuously increase in demand and utilisation.

AI refers to a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations or decisions influencing real or virtual environments.

Home-based care, or medical and supportive services provided in a patient’s home to help manage the patient’s health conditions, recover from illness or injury, or prevent hospitalisation, has experienced significant growth over recent years and is expected to face a compound annual growth rate of 7.9% between 2023 and 2030.

AI technology is applicable across a multitude of healthcare modalities and specialties and can meet a wide array of home-based patient needs. Current examples of AI applications in home-based care include Hospital at Home (HaH).

The HaH model enables the provision of acute care in patients’ homes and often leverages digital health technologies to provide home-based care.

These technologies sometimes incorporate AI to monitor, plan or augment care, seamlessly share information with the patient’s provider and allow for services that would traditionally be provided in an inpatient or outpatient setting to be shifted into the patient’s home.

Analysis of HaH performance has indicated reduced readmission or long-term care risk and higher patient satisfaction compared to in-hospital acute care. Advancement of AI and additional technologies such as wearables leveraged in HaH may serve to strengthen the care delivery model even further, driving wider recognition of value and use

Virtual rehabilitation (VRehab) seeks to improve patients’ physical and mental health and quality of life through home-based, virtual interventions. VRehab has shown similar outcomes to in-person rehabilitative care.

AI can play a role in various components of VRehab, including synthesis of patient data collected, measurement of patient progress, and delivery of personalised feedback to patients during their care. VRehab is currently undergoing significant growth and development.

Dozens of companies are emerging to offer at-home, AI-enabled rehabilitative care across various specialties, including stroke or traumatic brain injury recovery, pain management and management of substance use disorders.

AI is currently leveraged in the continuous monitoring and care of patients with chronic illnesses. Through analysis of patient data collected at home, AI identifies patients at risk of worsening illness and potential hospitalisation.

Furthermore, it creates and augments condition management strategies for review by a provider, cleans and organises patient-collected data, and directs patients to educational resources as needed.

Additionally, patient support tools such as AI-enabled chatbots have demonstrably been accepted by patients self-managing chronic conditions. These technologies are continuously being refined with efforts to improve patient-centricity, data integration and collaboration across various care stakeholders.

AI-enabled solutions are used for elderly patients at home to promote independence via key functions such as fall detection, medication management and monitoring of key health metrics.

These services can allow a patient to continue living independently (i.e., at home instead of within an assisted living centre) and can reduce the risk of future health complications or hospitalisation.

AI can also alleviate isolation in seniors via connective chatbots, games, and even strategies to improve quality of life for ageing patients facing diminished cognitive capabilities, such as personalised music therapy for those with Alzheimer’s Disease.

AI often requires access to various technologies, such as wearables, digital devices or smartphones, as well as the internet, potentially creating barriers to use.

Variability in US household income impacts ability to purchase and use these technologies; as of 2024, only 79% of US adults have access to home broadband for internet access, with access dropping to 70% for those aged 65 and older.

Establishing equity in access to AI-enabled home care requires consideration of strategies to mitigate these barriers.

With patient safety at the forefront, many stakeholders remain concerned about AI risks stemming from data biases and information privacy.

Care providers continue to vocally advocate against the notion that AI can be used to replace humans such as nurses or doctors, citing incidences of AI inaccuracies and errors that are corrected via human intervention.

Use of AI in any type of care requires thoughtful safeguards that can be continuously evaluated and evolve alongside the technology. Strategies such as the human-in-the-loop (HITL) approach, or ensuring that the AI systems are guided, communicated and supervised by human expertise, should continuously be applied to maintain safety and quality in care.

All AI technology implemented within home-based care should be vigorously vetted to ensure that data used to train the models is of high quality and free of bias as well as routinely tested for accuracy and reliability of outputs.

AI technologies will continue to rapidly advance in coming years. These advancements will likely create additional opportunities for use and integration into the delivery of healthcare within the home.

These uses have the potential to broaden access and improve quality but, above all, must be met with a commitment to safety and quality. 

Zachary Klein is a Consultant at Avalere Health and Brigit Kyei-Baffour is a Principal at Avalere Health