Future Directions for AI in Healthcare: Investigating Broader Applications of ChatGPT and Similar Technologies in Clinical Settings

One study looked at how ChatGPT performed in a special medical area: consultations for nose surgery. Researchers like Yi Xie tested it, and plastic surgeons such as David J Hunter-Smith helped review the results. They asked the AI nine example questions based on a checklist from the American Society of Plastic Surgeons. ChatGPT gave clear and simple answers about patient eligibility, surgery methods, risks, and what to expect after surgery.

For healthcare managers in the U.S., this shows that AI can help with teaching patients at an early stage. It can provide steady information any time of day. This might lower the amount of work for office and clinical staff, who usually answer common questions. But the study also points out some limits. ChatGPT gives general answers but cannot give advice tailored to each patient. This is important because understanding each patient’s needs and feelings helps manage their expectations and care better.

Medical managers and IT staff should see AI as a helpful tool, not a substitute for human judgment and emotional care. AI can support by giving quick replies and educational help, but final medical decisions and personal advice must come from trained healthcare workers.

Large Multi-Modal Models (LMMs) and Their Broad Applications in U.S. Healthcare

Besides language-only AI like ChatGPT, the World Health Organization (WHO) has given new advice on large multi-modal models (LMMs). These AI systems can work with different kinds of data, such as text, pictures, and videos. WHO lists five main healthcare uses for these tools:

• Diagnosis and Clinical Care: AI can help check symptoms, suggest possible diagnoses, and answer routine patient questions.
• Patient-Guided Symptom Investigation: Patients can use AI to better understand their symptoms before seeing a doctor.
• Clerical and Administrative Tasks: AI can summarize visits, create paperwork, and manage routine office jobs.
• Medical and Nursing Education: AI can make simulated patient cases for training purposes.
• Scientific Research and Drug Development: AI models can speed up research and data analysis.

For healthcare leaders in the U.S., these uses show that AI can affect not just patient care but also office work and staff training. But WHO warns about risks when using LMMs without proper checks. Wrong or biased information might lead to bad choices. People might rely too much on AI suggestions without thinking carefully.

In U.S. healthcare, where quality and rules are strict, using AI needs regular checks and clear reviews. This includes finding biases that affect different groups based on age, race, gender, or disability. Respecting these differences matches federal laws about fairness and privacy like HIPAA.

AI and Workflow Optimization in Healthcare Settings

AI such as ChatGPT and LMMs can help medical offices in the U.S. by automating front-office work and making daily tasks easier. This saves time, cuts mistakes, and lets staff focus on more important patient care.

Front-Desk Automation: Some companies use AI for phone answering in medical offices. Instead of staff answering every call, AI systems can sort calls, book or change appointments, give basic info, and pass harder questions to humans. This lowers wait times and lightens office work.

Appointment Management: AI linked to electronic health records can remind patients about appointments, update calendars in real-time, and change bookings when needed. This helps use clinic time better and cuts down on missed appointments, which can be costly.

Patient Triage Support: AI chatbots ask patients about symptoms and medical history early on. This helps doctors get ready and decide who needs care most quickly. It also guides patients on what to do next, like visiting the emergency room or scheduling a check-up.

Documentation Assistance: Writing clinical notes takes a lot of doctor time. AI tools can turn doctor-patient talks into organized notes for records. ChatGPT can also prepare patient education materials based on each case, helping patients understand and follow care better.

Billing and Claims Processing: AI can help billing by sorting claims, finding mistakes, and speeding up work. This part needs close attention to legal rules, but AI can lower office costs in U.S. practices.

For U.S. practice owners and IT managers, using these AI tools means being ready with technology and following rules. Protecting patient privacy, keeping AI secure, and updating software often are important steps.

Ethical and Governance Considerations within AI Deployment

The World Health Organization advises careful steps when adding LMMs and similar AI in clinics. In the U.S., these ideas mean health leaders should:

• Involve Many People: Developers and healthcare groups should include doctors, IT staff, patients, and researchers early. This helps find and fix biases and makes AI work better for real needs.
• Clear Rules and Checking: AI systems need policies that explain what they can and cannot do. It must be clear that AI does not replace a doctor’s judgment. Ongoing testing and checks after starting AI can find problems like errors or unfair effects on certain groups.
• Invest in Technology: Powerful AI needs strong computers and good data. Healthcare groups in the U.S. must spend to keep AI working well and available to many people.
• Follow Laws: AI in clinics must follow laws about patient safety, privacy, and non-discrimination. Local and federal agencies might create more rules, so healthcare managers have to stay updated.

Future Outlook and Practical Considerations for U.S. Medical Practices

AI like ChatGPT and multi-modal models show useful potential in healthcare areas, but American clinics are cautious about fully using them. Safety for patients, data accuracy, and trust in care remain very important. Right now, no AI can replace the detailed thinking and personal care that doctors provide.

At the same time, AI can handle simple repeated tasks, teaching, and early patient communication. This can help clinics use their resources better and improve how patients get care. Healthcare leaders need to balance benefits and risks by planning carefully, training staff on how to work with AI, and setting clear rules for using and watching AI tools.

Clinics wanting to use AI should check vendors carefully to make sure their technology follows ethical and federal health rules. Ongoing training about what AI can and cannot do is important to prevent staff from relying too much on AI or misunderstanding its advice.

Medical practice owners and managers in the U.S. play an important role in guiding AI use. Using AI in communication, office work, and patient education can improve operations but must be managed carefully. They need to pay attention to new research, guidelines, and rules from groups like the WHO.

By using ChatGPT and LMMs the right way, U.S. healthcare providers can gradually improve efficiency and patient interactions. The focus should be on AI supporting human care, not replacing it.