Exploring the transformative journey of healthcare, shifting from hospitals to the comfort of home.
Mass General Brigham recently partnered with Best Buy to enhance their Healthcare @ Home service. This initiative responds to the growing preference for at-home medical care and aims to address workforce shortages while improving health outcomes.
The trend towards Hospital Care at home began in 2020 with the CMS's Acute Hospital Care at Home waiver. Since then, Mass General Brigham has treated over 3,000 patients at home, reducing costs by nearly 40% compared to in-hospital care. Benefits included fewer lab tests, less imaging, less sedentary time for patients, and a 70% lower readmission rate within 30 days.
McKinsey estimated that by 2025, up to $265 billion, or 25% of total care costs, could shift to home-based services for Medicare beneficiaries. The U.S. healthcare model is evolving to include more home and virtual health services.
Organizations like Moving Health Home, which includes Ascension, Intermountain Health, MGB, Amazon Care, and Best Buy, are advocating for home-based clinical services. They support services like in-home primary care and dialysis, which can lower hospital costs and improve patient outcomes.
However, there are a myriad of challenges which Healthcare Organizations face, in driving Healthcare @Home, including.
• Limited access to specialists in the home setting.
• Fragmented healthcare data impeding effective monitoring.
• Difficulty in maintaining patient engagement and adherence to treatment plans.
• Resource and workforce constraints limiting home healthcare availability.
So far, I’ve focused on 3 solutions which I believe could drive broader adoption, enabled by Artificial Intelligence. Remote Process Monitoring, Intelligence Automation & Remote Process Automation.
IA This technology blends the use of AI to simulate human actions and decision-making with the efficiency of automation. Generative AI contributes to this by generating patient communication and documentation, effectively reducing the time healthcare providers spend on administrative tasks. Predictive AI in intelligent automation could, for instance, analyze historical patient data to forecast future health events or needs, allowing for preemptive care measures that could be managed remotely.
Generative AI can be used to develop advanced patient monitoring systems that can generate alerts and recommendations based on real-time data analysis. Predictive AI takes this a step further by interpreting the monitored data to predict potential health issues before they become critical, facilitating early intervention and potentially avoiding emergency situations.
RPA utilizes AI to perform repetitive tasks that were previously done by humans. With the addition of generative AI, these tasks can now include complex decision-making processes such as interpreting patient data and even suggesting treatment plans. Predictive AI can be used to optimize these automated processes by predicting when and where resources will be needed, thus improving efficiency and patient outcomes.
Personalized Care Plans: Generative AI can create individualized treatment plans by analyzing patient data and ongoing health trends, while Predictive AI can forecast how the patient's condition may change over time, allowing for dynamic adjustments to the care plan.
Virtual Health Assistants: AI-powered virtual assistants can provide patients with real-time health advice and reminders for medication, leveraging Generative AI to tailor conversations and Predictive AI to anticipate patient needs based on their health routines.
Medication Management: Predictive AI can monitor a patient's medication intake and predict potential adverse drug reactions or interactions, while Generative AI can assist in the creation of medication schedules and guidelines for patients.
Telehealth: Generative AI can improve telehealth services by generating post-consultation summaries and follow-up plans. Predictive AI can be used to identify patients who may require a telehealth consultation based on their health data trends.
Advanced Diagnostics: Generative AI can assist in diagnosing conditions by synthesizing information from various medical sources and patient records, while Predictive AI can identify patterns in data that may indicate the early onset of a disease.
These advancements in AI technology not only enhance patient care but also streamline the workflow for healthcare providers, making the home a more effective and efficient site for healthcare delivery. As these technologies continue to evolve, they will likely unveil even more innovative solutions to support the growing demand for home healthcare services.
• CVS Health and Amazon (2018): Home delivery of medical supplies.
• Walgreens and Microsoft (2019): Digital health platforms for remote monitoring.
• Humana and Honor (2020): In-home care services for Medicare Advantage members.
• Kaiser Permanente and Apple (2021): Integrating Apple Watch data with health records.
• Mayo Clinic and Google Cloud (2022): Cloud-based platform for remote consultations.
• Optum and Samsung (2023): AI-powered solutions for remote monitoring.
These partnerships highlight the collaboration between healthcare and technology companies to enhance at-home care.
