The healthcare system in the United States is changing with many new technologies. One important tool in this change is artificial intelligence, or AI. AI is playing a big role in how healthcare is given, how administrations work, and how patients get involved. But these changes bring new ethical questions and challenges, especially about keeping patient freedom and helping healthcare workers in care settings.
Healthcare leaders, medical practice owners, and IT managers in the U.S. have an important job: to add AI technologies while keeping the human parts of medicine. This article looks at how to include human centeredness in AI health tools, focusing on ethics, patient freedom, and making work easier for healthcare teams.
A study from Elsevier Ltd. looked at 253 articles from 2000 to 2020. It offers a clear guide for using AI ethically in healthcare. This guide is called the SHIFT framework. SHIFT means Sustainability, Human centeredness, Inclusiveness, Fairness, and Transparency. It helps AI developers, healthcare workers, and policy makers.
This guide is very important in the United States because of its diverse people and complex healthcare systems. AI must meet many types of patient needs and social situations.
AI is helpful for diagnosis, treatment advice, and office work. But it is important that AI stays focused on patients and does not make care less personal. AI often works like a “black box,” where its choices are hard to understand for doctors or patients. This can cause people not to trust it. In the U.S., this makes it harder to accept and follow AI advice.
There is a worry that AI might reduce feelings of care, trust, and personal attention. These are important for good health outcomes and strong doctor-patient bonds. Research shows AI should not replace the human connection in healthcare. Instead, it should help doctors spend more time with patients.
Doctors in the U.S. say AI should be made to support, not take over, caring parts of medicine. AI can help by doing routine tasks, which lets doctors focus on hard decisions and kind communication.
Patient autonomy means respecting a person’s right to make choices about their healthcare. In the U.S., this is a key idea backed by law and ethics. AI must be clear and explainable enough to help doctors and patients decide together.
AI can be unfair if its data does not represent all groups well. This can make healthcare inequality worse, which is a big worry in America’s mixed society. To be inclusive, AI tools must treat people fairly no matter their race, income, or age. This stops ignoring or mistreating vulnerable groups.
Patient-focused AI needs:
Even though AI brings benefits, U.S. healthcare places face problems using it fairly. AI changes fast, so clear rules and management are needed to use it well. The studies found several problems:
Healthcare groups and policy makers must invest in data systems, train staff to use AI well, and create teams that include IT, clinical, and office workers.
Medical students in the U.S. feel hopeful about AI but stress the need for ethical rules and patient focus. Future doctors know they must use AI while keeping patients in charge and keeping their own judgment.
Medical schools are starting to teach AI and ethics to prepare new doctors to use AI responsibly. This helps make sure AI supports human decisions rather than replaces them. Teachers aim to help students explain AI advice clearly so patients can understand and trust it.
Health workers need to balance using AI with keeping kind, personal care. This means managers must create ways to use AI daily without losing the human side of medicine.
AI-driven automation can help U.S. medical offices work better, especially with front-office and admin tasks. Hospital managers, practice owners, and IT leaders can improve workflow with AI, lowering costs, helping patients, and freeing staff from boring tasks.
AI phone automation is an example. It helps healthcare without losing human care values. Companies like Simbo AI use AI to handle patient calls, schedule appointments, send reminders, and answer basic questions. This technology can:
Using AI for phone and patient contact keeps human connection strong. It lets staff focus on harder patient needs instead of routine talk. This fits well with the SHIFT ideas of lasting, fair, human-focused, and clear AI.
As AI grows quickly, U.S. healthcare groups must adjust their plans based on local patients, laws, and cultures.
Admins and IT staff need to:
Using AI the right way means knowing healthcare is more than data or programs. It is about people getting caring, personal treatment. So, AI in U.S. healthcare should first help workers and patients, not replace them.
Research keeps being needed to improve AI rules and build ethical, practical AI in U.S. healthcare. The review of many studies from 2000 to 2020 shows that responsible AI growth relies on:
This steady work will help U.S. healthcare find the right balance between the benefits of AI care and medicine’s core values—respect, kindness, and fairness.
The growing use of AI in healthcare brings chances to improve diagnosis, make work more efficient, and involve patients better. But in the United States, where patients are many kinds and healthcare is complex, AI must stay focused on people to protect patient freedom and help healthcare workers. Frameworks like SHIFT offer a clear plan for using AI well. Also, AI tools like Simbo AI’s front office systems show how AI can help without losing human touch. By carefully balancing ethics with new technology, healthcare leaders and IT managers can bring AI tools that help both patients and providers.
The core ethical concerns include data privacy, algorithmic bias, fairness, transparency, inclusiveness, and ensuring human-centeredness in AI systems to prevent harm and maintain trust in healthcare delivery.
The study reviewed 253 articles published between 2000 and 2020, using the PRISMA approach for systematic review and meta-analysis, coupled with a hermeneutic approach to synthesize themes and knowledge.
SHIFT stands for Sustainability, Human centeredness, Inclusiveness, Fairness, and Transparency, guiding AI developers, healthcare professionals, and policymakers toward ethical and responsible AI deployment.
Human centeredness ensures that AI technologies prioritize patient wellbeing, respect autonomy, and support healthcare professionals, keeping humans at the core of AI decision-making rather than replacing them.
Inclusiveness addresses the need to consider diverse populations to avoid biased AI outcomes, ensuring equitable healthcare access and treatment across different demographic, ethnic, and social groups.
Transparency facilitates trust by making AI algorithms’ workings understandable to users and stakeholders, allowing detection and correction of bias, and ensuring accountability in healthcare decisions.
Sustainability relates to developing AI solutions that are resource-efficient, maintain long-term effectiveness, and are adaptable to evolving healthcare needs without exacerbating inequalities or resource depletion.
Bias can lead to unfair treatment and health disparities. Addressing it requires diverse data sets, inclusive algorithm design, regular audits, and continuous stakeholder engagement to ensure fairness.
Investments are needed for data infrastructure that protects privacy, development of ethical AI frameworks, training healthcare professionals, and fostering multi-disciplinary collaborations that drive innovation responsibly.
Future research should focus on advancing governance models, refining ethical frameworks like SHIFT, exploring scalable transparency practices, and developing tools for bias detection and mitigation in clinical AI systems.
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