Chronic diseases like diabetes, chronic kidney disease (CKD), high cholesterol, and heart disease affect many people in the United States. There are over 29 million people diagnosed with diabetes, and one in seven Americans has CKD.
The growing number of these conditions creates pressure on healthcare providers and systems. Many healthcare organizations use value-based care models like Accountable Care Organizations (ACOs) in Medicare’s Shared Savings Program. In 2023, ACOs saved more than $2.1 billion by using data to better manage chronic diseases. CMS also gave over $3 billion in rewards to ACOs that showed good care for chronic conditions.
Caring for chronic diseases means watching patients closely, acting quickly when needed, and having patients help with their care. This puts a lot of work on healthcare staff, especially care coordinators and doctors who manage many patients and try to give personal care.
Artificial intelligence (AI) offers tools to help with these problems. It can do administrative work automatically, help doctors make decisions, and improve communication with patients. Managers can use AI to support care coordinators and clinicians, giving them more time to spend with patients.
AI helps make care plans that fit individual patients by studying different data types. This includes electronic health records, lab results, social factors, and what patients report. Lab tests give up-to-date health information that can catch risks early and track disease progress. Companies like Labcorp have built systems using lab results with location and population data to find patients who need more care.
Devices for remote patient monitoring (RPM) use cellular networks to send health details like blood pressure, blood sugar, or heart rate all the time. Healthcare workers get alerts quickly and can change care before problems get worse. Virtual care programs that combine AI with RPM provide ongoing help outside the clinic. This lowers hospital visits and helps patients stay healthier.
AI tools make it easier to talk with patients between visits. AI messaging systems answer questions fast, give educational materials in ways patients understand, and remind patients about medicines and appointments. These help patients follow their care plans better.
Alex Ramirez, Director of Enterprise Clinical Quality and Training at ChartSpan, says AI helps connect technology with human care. It supports clinicians but does not replace the work of care coordinators. AI tools that check patient calls and analyze moods make sure care quality is good. They also help staff improve their communication skills.
It is hard to get steady quality care in rural or underserved places. AI-powered virtual care tools help by letting patients get monitoring, consultations, and care without traveling. These tools remove distance problems and help people manage chronic diseases continuously.
Medical practices spend a lot of time on tasks like scheduling, paperwork, and communicating with patients. About 40% of U.S. doctor offices now use AI for administrative jobs. AI automation can make these tasks faster and help reduce burnout for doctors and staff managing chronic diseases.
AI systems like Simbo AI handle incoming patient calls, bookings, and reminders. This lowers wait times on the phone and lets staff focus on harder tasks.
Automated follow-up messages remind patients about lab tests, refilling medicines, or telehealth visits without needing staff to do it manually. These reminders help patients stay involved in their care.
Writing clinical notes takes a lot of time, but AI tools can help by transcribing, organizing, and checking notes. ChartSpan’s AI checks every patient call to make sure it meets Medicare and Medicaid rules. If something is missing or wrong, human staff are alerted.
By automating checks, clinics lower the chance of billing mistakes and penalties, which is important when caring for chronic diseases using value-based care plans.
AI examines patient data to find those at higher risk of serious problems. This lets care coordinators and doctors focus on these patients first, use resources well, and set personalized care goals.
AI can also provide lists of local community resources, like food banks or transportation help, which support social needs tied to chronic disease care.
While AI has many benefits, healthcare leaders must also handle concerns about clarity, privacy, and responsibility.
The American Medical Association (AMA) says AI use in healthcare must be clear. Doctors need to know when AI affects decisions. AMA President Dr. Jesse M. Ehrenfeld says, “Doctors who use AI will replace those who don’t,” meaning clinicians must learn how to use AI and keep a human role in care.
Doctors worry about AI possibly introducing bias, risking patient privacy, or giving wrong results. Practices using AI should follow HIPAA rules, test tools carefully, and keep human oversight.
AMA also calls for good control of AI in healthcare, including clear sharing of information, privacy protections, and ethical use. Administrators and IT staff should work with clinical leaders to meet these rules while using AI.
Healthcare organizations in the U.S. face more rules, patient needs, and competition. Using AI to improve patient engagement and chronic disease care helps with several goals:
By using AI for patient engagement and automating workflows, U.S. medical practices can improve care for chronic diseases, raise patient satisfaction, and meet modern healthcare demands. As AI tools grow, combining them with human skills will be important for lasting success in care and health outcomes.
AI is used in healthcare for developing cancer prognosis, responding to patient messages, predicting clinical outcomes, providing documentation support, and recommending staffing volumes.
Physicians are concerned about AI exacerbating bias, compromising privacy, introducing new liability concerns, and providing misleading conclusions.
As of last fall, the FDA had approved 692 AI or machine-learning medical devices, primarily in radiology, cardiology, and neurology.
Transparency is critical for ensuring trust, helping physicians understand AI processes, and ensuring ethical use of AI technologies.
The AMA’s advocacy principles focus on AI oversight, transparency in disclosures, liability issues, data privacy, and governance.
AI is expected to enhance diagnostic accuracy, personalize treatments, and reduce administrative burdens, transforming how healthcare is delivered.
About 40% of U.S. physician practices are using some form of AI, mostly for administrative tasks.
‘The human in the loop’ refers to physicians remaining aware of AI algorithms influencing clinical decisions, allowing them to intervene as needed.
Physicians face challenges in understanding how input data influences AI outputs and recognizing the training data for AI tools.
There is significant potential for AI tools to enhance patient engagement in their health and help manage chronic conditions.
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