5 Questions to Prepare for Generative AI in Healthcare

1. How Can Health Systems Prepare for the Next Stage of AI?

Healthcare organizations must educate their workforce on the use of AI technologies through training programs specific to each AI system. These training programs should teach providers about the limitations of such technologies and the continued need for physician oversight and review of AI outputs.

Organizations must also prepare and offer resources to address patient mistrust in the use of AI technologies. Resources should include materials that adequately inform patients about the role of AI in the care they will receive and demonstrate that sufficient privacy and security protocols are in place to protect data gathered and used by the AI system itself.

2. How Can Generative AI Tools Address Workforce Issues?

Whether through recruitment tools, scheduling assistance or even personalized training programs, generative AI streamlines both administrative and patient workflows. This, in turn, may reduce burnout for providers and administrative staff.

It also allows providers to spend more time directly with patients, potentially improving access to care, quality of care, patient experience and, ultimately, care outcomes.

READ MORE: Find out how to avoid four common AI mistakes.

3. Where Can Generative AI Best Add Value to a Health System? 

AI can revolutionize workflow processes by automating routine tasks that take significant time and human labor. For example, generative AI can address various billing and claims processes and reduce potential billing and coding errors. Generative AI also can assist with patient intake processes and medical record collection and retention.

4. Are There Security or Privacy Concerns Around Generative AI? 

Security and privacy concerns that arise with generative AI generally surround potential misuse of patient protected health information to support the continuous learning of the AI system itself. Without direct informed consent by patients, collecting and using patient data for this purpose can raise significant privacy concerns.

Moreover, the use of such data, especially where the health organization does not own the AI system, may present additional security concerns, including the increased risk of data leakage or data breaches.

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5. What Impact Could Generative AI Tools Have on Health Equity Goals?

Generative AI can improve access to care, care outcomes and patient experience. However, the legal and ethical considerations that arise with AI-based technologies may raise substantial concerns and mistrust from the public at large.

For example, bias can significantly impact overall health outcomes of not only individuals but entire health communities, especially disadvantaged populations. Moreover, a lack of sufficient privacy and security protocols puts both the patient and the health organization at risk. This includes, as described above, the potential for increased risk of data leakage or data breaches of patient protected health information.

Overall, it is imperative that health organizations implement sufficient administrative, technical and physical safeguards to protect patient data when using AI systems.

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This post originally appeared on TechToday.

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