Artificial intelligence (AI) is being used more in healthcare across the United States. It helps with diagnosing patients and managing paperwork. AI can change how doctors and hospitals work. But as AI tools become more common, it is very important to use them in honest and careful ways, especially in medical settings. This article talks about these important issues for medical managers, owners, and IT staff who pick and manage AI systems.
Surveys show that many doctors are open to using AI in healthcare. A survey by the American Medical Association (AMA) asked 1,081 doctors. About 66% said AI has benefits. But only 38% were using AI in their work at the time. Many doctors are excited about AI helping with diagnosis (72%), making work easier (69%), and better patient health results (61%). This shows many like the idea of AI, but fewer have started using it.
Even with this excitement, some doctors have concerns. About 41% feel both hopeful and worried about AI’s effect, especially about how it might change the patient-doctor relationship and patient privacy. These worries show why careful planning is needed when adding AI to healthcare.
AMA President Dr. Jesse M. Ehrenfeld said human involvement is very important in AI care. He said that even though AI can help with decisions, patients must know a person is still in charge of their care. It is important to have clear points where humans oversee AI to keep good medical judgment and protect patient care.
One big challenge with AI in healthcare is a lack of transparency. Transparency means doctors and patients understand how AI tools make decisions or suggestions. This helps build trust. It also allows doctors to check and question AI results.
The AMA’s AI Principles say transparency is an important ethical value. For example, when AI is used to decide insurance claims, insurers should say they use AI. They need to provide public data on claim approvals, denials, and appeals so people can check. Being open helps keep AI systems under control and stops machines from replacing needed human review.
Transparency also means clear details about how the AI was made, what data it uses, and its limits. Duke Health’s ABCDS Oversight Committee says transparency is an important ethical concern. They require teams to say what social and demographic data the AI models use. They also report how those data affect results. Transparency helps make AI fair and trustworthy.
Regulators in the United States focus more on transparency to keep AI safe in healthcare. Clear rules help doctors trust AI. Also, ongoing checks on AI after it is released help keep it working well and safely.
AI systems in healthcare should follow ethical ideas like fairness, safety, privacy, and respect for people. The AMA wants AI to be made and used responsibly so it does not cause unfair results. AI should not treat people differently because of race, gender, money, or where they live.
Bias can happen in AI in different ways:
To stop bias, a careful review is needed from creating AI to using it in healthcare. Duke Health’s ABCDS committee checks fairness by asking questions about using social and demographic data. They work with the developers to reduce bias before AI is used with patients. For example, removing one demographic factor made the AI fairer while still working well.
Ethical use also means keeping patient data private and safe. Using AI quickly should not put patient confidentiality or consent at risk. Groups like UNESCO support the importance of human rights and dignity. They promote ethical AI worldwide. These international rules help efforts in the United States to stop AI from making inequalities worse or breaking patient rights.
AI can quickly analyze lots of data, but it should not replace human judgment in medicine. AMA leaders say AI decisions must have clear points where humans check them. This keeps doctor expertise and protects patient care quality.
In real life, AI suggestions like diagnosis or treatment plans should be reviewed and understood by doctors. This keeps the connection between patient and doctor strong. It also makes sure decisions consider patient situation beyond what AI can see.
Human checks also catch mistakes or problems AI might cause. For medical managers and IT staff, this means setting up workflows and rules so doctors stay involved while using AI help.
AI helps healthcare by automating tasks. A lot of doctors’ time goes to paperwork and admin work. This causes stress and less focus on patients. AI can do repeated tasks, make work smoother, and improve efficiency.
Examples of automation include:
When these tasks are automated with transparency and human checks, clinics can make care easier for patients, reduce errors, and improve how care is coordinated.
Bringing AI into healthcare is not simple and has challenges:
Healthcare managers and IT staff have an important job. They must choose AI tools that are clear, support human checks, and follow ethical rules like those from the AMA and regulators.
As AI becomes part of healthcare, medical staff need to learn how to use it well. The AMA created basic AI education materials for doctors and trainees. These help them understand what AI can do, its limits, and ethical issues.
Teaching medical staff and managers about AI helps them make smart decisions and work well with AI developers. Knowing both the good and bad sides of AI helps hospitals use it without hurting ethics or patient trust.
In the United States, there are ongoing efforts to encourage safe and trustworthy AI in healthcare. The AMA’s AI Principles and rules aim to set standards for safety, fairness, honesty, and responsibility.
The European Union has new AI laws like the Artificial Intelligence Act, effective in 2024. These laws cover high-risk AI systems such as medical devices. The rules focus on reducing risks, keeping humans involved, and having good quality data. This offers an example of strong AI rules.
Worldwide, groups like UNESCO support ethical AI based on human rights, fairness, and transparency. They provide tools like Ethical Impact Assessments to help hospitals use AI responsibly.
Working together — regulators, AI makers, medical workers, and managers — is key to making good policies that keep patients safe and provide fair healthcare access.
Adding AI tools in medical care brings possible benefits but also raises important questions about ethics and openness. Medical managers, owners, and IT staff in the United States need to carefully check AI systems for fairness, bias, patient privacy, and clarity before using them.
Keeping human checks in AI decisions helps keep quality patient care while using AI’s abilities. Automating tasks can lower work and improve clinic operations if AI is made responsibly and fits well with existing work.
Successful AI use depends on ongoing learning, clear communication, ethical management, and teamwork with healthcare workers. By focusing on these rules, healthcare groups can use AI in ways that help patient care and make clinics run better.
Nearly two-thirds of physicians surveyed see advantages in using AI in healthcare, particularly in reducing administrative burdens and improving diagnostics, but many remain cautiously optimistic, balancing enthusiasm with concern about patient relationships and privacy.
Transparency is critical to ensure ethical, equitable, and responsible use of AI. It includes disclosing AI system use in insurance decisions, providing approval and denial statistics, and enabling human clinical judgment to prevent automated systems from overriding individual patient needs.
Human review is essential at specified points in AI-influenced decision processes to maintain clinical judgment, protect patient care quality, and uphold the therapeutic patient-physician relationship.
About 39% of physicians worry AI may adversely affect the patient-physician relationship, while 41% raise concerns about patient privacy, highlighting the need to carefully integrate AI without compromising trust and confidentiality.
Trust can be built through clear regulatory guidance on safety, pathways for reimbursement of valuable AI tools, limiting physician liability, collaborative development between regulators and AI creators, and transparent information about AI performance and decision-making.
Physicians see AI as most helpful in enhancing diagnostic ability (72%), improving work efficiency (69%), and clinical outcomes (61%). Other notable areas include care coordination, patient convenience, and safety.
AI is particularly well received in tasks such as documentation of billing codes and medical notes (54%), automating insurance prior authorizations (48%), and creating discharge instructions, care plans, and progress notes (43%).
The AMA advocates for AI development that is ethical, equitable, responsible, and transparent, incorporating an equity lens from initial design stages to ensure fair treatment across patient populations.
Post-market surveillance by developers is crucial to continuously assess safety, performance, and equity. Data transparency allows users and purchasers to evaluate AI effectiveness and report issues to maintain trust.
Foundational knowledge enables clinicians to effectively engage with AI tools, ensuring informed use and collaboration in AI development. The AMA offers an educational series, including modules on AI introduction and methodologies, to build this competence.
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