Navigating the Ethics of AI in Healthcare

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Artificial intelligence is revolutionizing how institutions evaluate and treat patients while improving their overall experience with the health system. AI technology is capable of drawing on vast reservoirs of data to identify risks and escort patients through complex systems at speeds that simply aren’t possible for human beings alone.

While AI is playing a critical role in saving lives and improving accessibility, it’s still considered a supplemental tool for professionals in care and administrative roles. If AI isn’t utilized properly, these systems can easily introduce ethical challenges that negatively affect patient outcomes. Courses like Artificial Intelligence in Medicine: Innovations Shaping Healthcare Today help nurses, administrators, and allied health workers understand the following four principles for deploying AI technology ethically and effectively in the workplace.

1. Informed Consent

Patient consent is the foundation of ethical care, and relevant information and potential risks always need to be explained clearly and thoroughly. Whether it’s relatively harmless testing or a major surgical intervention, patients have a right to know how their caregivers are formulating their recommendations and where this information comes from.

Healthcare professionals using AI should be prepared to explain:

• What tools were used to arrive at these results?
• How was this data generated?
• Will this information be stored and used in the future?
• Why is it relevant?
• How reliable are these insights?

This is especially important when introducing new technologies like AI to reduce anxiety and ensure patient comprehension as they make critical personal decisions about their health. If they give consent, it should be documented in a way that can be referenced and shared among other members of the healthcare team.

The Challenges of Informed Consent with AI Systems

In practical terms, artificial intelligence introduces complexities to the consent process that may not align well with traditional standards. Because AI offers the potential to manage extreme amounts of information with a broad far reach, physicians, nurses, and administrators should consider the following to avoid overwhelming or confusing patients:

• How much information are patients expected to be made aware of?
• What is the best way to explain the use of complex AI tools?
• Does the patient have enough relevant information to evaluate options and risks?
• Are there any concerns that can be explained more thoroughly?

Every situation may require a different balance of each of these factors, and it’s up to care teams to evaluate the most ethical approach for a particular patient and their family.

2. Data Bias

The potential for biased analysis is central to the ethics of AI in healthcare. Bias occurs when data sets or algorithms adversely affect model behavior and results. If health professionals don’t understand how and why these biases occur, it can quickly lead to decisions that discriminate against certain groups of individuals or deliver low standards of care.

A 2019 study of racial biases in AI health systems illustrated the impact a poor algorithm can have on an entire segment of the population. By prioritizing health spending as a metric, the system concluded that black women were in better health overall than white women because proportionally less was spent on their care. In fact, this statistic demonstrates exactly the opposite conclusion when contextualized by other relevant factors.

When these biases are brought to patients, a subsequent loss of trust in the organization using the AI technology may occur. These issues can quickly spread to legal and regulatory entities, and guarding against data bias when using AI starts with internal governance. Leadership should employ best practices like regular audits, assessments, bias detection tools, and maintaining a culture of transparency.

3. Transparency

Organizations using AI technology must offer a clear explanation of how AI is being deployed or integrated into their operational processes. This includes systems that handle resource allocation and management in addition to care-related tools.

Also, cultural transparency allows for a system of checks and balances or scrutiny about how information is being used. This also allows stakeholders on a higher organizational level to confirm that the use of AI is still aligned with the organization's mission, vision, and values. By embracing transparency around AI investments, leaders can promote a culture of accountability that protects both institutions and patients from potential harm.

4. The Role of Organizational Leaders

The ethical use of artificial intelligence in any organization begins with leadership. Any new technology—especially tools like artificial intelligence—will come with questions and hesitation from employees, patients, and regulatory agencies alike. Administrators on all levels should ensure there is an institution-wide commitment to ethical AI principles to maintain trust with consumers and users.

When implementing AI systems, leadership should consider:

• Reputational risk: If technology is used inappropriately, it may harm future professional and public buy-in.
• Regulatory and legal risk: A lack of documentation, security, and legal/ethical evaluation can expose institutions to serious financial penalties.
• Investment risk: AI systems often require high-quality training and infrastructure to properly implement. Without proper support, these tools can quickly lose value for employees and patients alike.

Success with AI in healthcare begins with organizational leaders having a working knowledge of best practices and ethics of AI in healthcare. By staying informed, they can protect their investment while providing valuable resources for the people they serve.

Become Familiar with the Ethics of AI in Healthcare

New technology always introduces fresh ethical questions, and integrating AI into existing healthcare systems means having a thorough knowledge of the risks it presents. Staff on every level should be aware of the best practices and potential pitfalls surrounding these tools and the variety of applications they can expect to encounter in the workplace.

Premiere is committed to ensuring doctors, nurses, administrators, and other allied health professionals understand the ethics of AI in healthcare and how to make the most of these valuable systems. Courses like Artificial Intelligence in Medicine: Innovations Shaping Healthcare Today deliver the latest information and expert guidance on how healthcare workers can ethically and responsibly engage with AI in the workplace.

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