Precision health is a way of treating people that looks at their genes, health history, lifestyle, and surroundings. Instead of giving the same treatment to everyone, it tries to match care to each person’s needs. This can help avoid treatments people do not need, make health results better, and lower costs.
Artificial intelligence (AI) helps make precision health possible. AI uses smart computer programs to study lots of medical data. It can predict who might get sick, help doctors make better diagnoses, create treatment plans just for one person, and see how a disease might change over time. Dartmouth’s Center for Precision Health and Artificial Intelligence (CPHAI) shows how AI is moving forward in healthcare. With $2 million in funding from the Geisel School of Medicine and Dartmouth Cancer Center, CPHAI works on tools to help doctors make better decisions by studying data.
The market for AI in healthcare is growing fast. It was worth almost $5 billion in 2020 and is expected to be more than $45 billion by 2026. This growth shows there is a strong need for healthcare workers trained to use AI in both clinical care and administration.
As AI and precision health tools become more common in clinics and hospitals, health workers need to know what these tools can and cannot do. Medical practice administrators and IT managers help bring in and manage these tools. But training many workers remains difficult. A well-educated workforce in AI and precision health is important to:
CPHAI in New Hampshire offers learning and research for medical residents, students, and professionals. It shows that education in AI and health involves many parts, including technology, ethics, and society.
The American Medical Association (AMA) uses the term “augmented intelligence” to show that AI supports human thinking, not replaces it. They say AI tools should be made and used in fair, clear, and careful ways to help doctors and improve patient care.
Recent AMA studies found that AI use by doctors in the U.S. rose from 38% in 2023 to 66% in 2024. Also, 68% of doctors see some benefits of AI tools in daily work. This means AI is no longer new but part of regular medical work.
Because of this, education is needed to help doctors learn:
The AMA supports teaching about AI in medical schools and residency programs. This helps new doctors work well with AI systems and use them safely.
AI is also useful in healthcare management. It can reduce work stress and make operations more efficient. Medical practice leaders and IT managers face tasks like scheduling, billing, communication, and patient care. AI can automate some of these tasks.
An example is Simbo AI, which automates front-desk phone calls. Calls are important for booking and questions, but too many calls can overwhelm staff. Simbo AI uses AI to handle call routing, appointments, cancellations, and general questions without a person answering every call. This frees staff to focus on other tasks and helps patients get better service.
AI helps with scheduling by predicting when patients might miss appointments and by spacing bookings well. It also helps with billing by speeding up insurance processing and reducing mistakes. These are key parts of running a healthcare practice efficiently.
AI helps doctors like radiologists and pathologists by sorting medical images and cases. It can find urgent problems faster and spot disease signs early. This helps doctors work faster and improves patient care.
AI works best when healthcare organizations have workers who understand it well. This includes knowing what AI does, its benefits, and risks. Healthcare systems in the U.S. need to build education programs for all staff, including administrators, clinicians, and IT teams. These programs should teach:
Dartmouth’s CPHAI shows how education combining medicine, data science, ethics, and computer science can prepare people for AI roles. Groups like the AMA give advice to help workers use AI carefully and well.
By training medical practice administrators, owners, and IT managers in AI, healthcare centers can use AI smoothly and improve patient care and operations.
Precision health needs many kinds of data, including genes, medical records, lifestyle habits, and environment. Future health leaders need knowledge in medicine and also skills to use and understand AI and complex data.
Schools across the U.S. are starting to teach AI and precision health ideas. These programs train students to combine medical understanding with computer tools thoughtfully and well.
Since the AI healthcare market is growing fast, it is important to attract students to this field. Centers like Dartmouth’s CPHAI help students and workers get involved in AI research, ethics, and new medical ideas.
State and local governments and healthcare groups should work together to expand access to education and training. This helps build a workforce that can keep up with fast changes and supports fair healthcare for everyone.
Using AI in healthcare brings problems related to fairness, privacy, and trust. Some of these are:
Groups like the AMA and CPHAI work on policies that make sure AI is fair and responsible. Education programs must teach healthcare workers about these ethical issues so they understand the social impact of their work, not just the technical side.
Administrators and IT managers are the link between technology and patient care. How well they understand AI affects how well it works in medical practices.
To keep up with healthcare changes, they need to:
Training designed for administrators and IT managers with a mix of tech and healthcare knowledge will help them use AI well and carefully.
Teaching about AI and precision health fits with current healthcare changes such as:
Workers trained in these areas are better prepared for new technology roles. This keeps healthcare organizations adaptable and better at helping patients.
For medical practice administrators, owners, and IT managers in the United States, learning about AI and precision health education is more important than ever. Training programs help ensure healthcare can use AI well in both patient care and management. Schools, healthcare groups, and professional organizations working together build the base for the next generation of professionals to manage AI responsibly while keeping patients first.
The CPHAI aims to improve health outcomes by leveraging biomedical data through AI, focusing on personalized health care and developing innovative solutions to clinical challenges.
Saeed Hassanpour, an associate professor specializing in biomedical data science, epidemiology, and computer science, serves as the inaugural director of CPHAI.
Precision health is a holistic approach that personalizes treatments and prevention strategies based on an individual’s unique biology, including genetics, medical history, lifestyle, and environment.
CPHAI will develop AI-driven diagnostic tools, optimize treatment strategies, analyze biomedical data, and create digital technologies that assist health care providers in decision-making.
AI helps in extracting valuable insights from complex biomedical data, predicting disease risk, enhancing diagnostic accuracy, and tailoring treatment plans based on individual patient data.
CPHAI focuses on the ethical use of AI by tackling issues such as algorithmic bias, improving data transparency, privacy, and ensuring equitable health care outcomes for diverse populations.
CPHAI will create educational opportunities in AI and precision health, aiming to develop a skilled workforce and attract students and professionals to the Upper Valley region.
The market for AI in health care is expected to grow from nearly $5 billion in 2020 to over $45 billion by 2026.
CPHAI will collaborate with multiple departments and institutes, including the Geisel School of Medicine, Dartmouth Cancer Center, Thayer School of Engineering, and others to enhance interdisciplinary research.
CPHAI will actively engage with local and global communities to consider their perspectives and needs in AI technology development, fostering trust and awareness regarding AI’s benefits and potential risks.
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