AI in Healthcare: Navigating Opportunities, Challenges, and Ethical Concerns

HIMSS25 was loaded with transformative sessions about adopting healthcare efficiencies through analytics and Artificial Intelligence (AI), and bustling with AI vendors and investors seeking to transform healthcare delivery. One AI-focused session I found particularly compelling was HL7 AI Standards: Provenance, Fraud Detection, Prevention & Health Equity led by Dr. Julia Skapik, Board Chair at HL7 International, as it called for a patient-centered plan for leaders in the healthcare ecosystem. Here are some of my takeaways from the session.

While AI has been steadily transforming the landscape of patient care, diagnostics, and medical research, its integration into healthcare also raises significant concerns related to patient safety, ethics, and the regulatory environment. Opportunities are vast; yet, we must carefully consider unprecedented technical challenges and ethical concerns which require a patient-centric approach. 

AI is a tool for frontline healthcare workers to flag potential health risks, assist in surgeries, and analyze medical imaging scans. On the administrative end, AI can be used to analyze enormous data sets for clinical research and assist in scheduling and billing workflows to significantly reduce administrative burden. 

Nonetheless, AI challenges in healthcare create significant hurdles for adoption and implementation

1. Trust: There is a lack of transparency in AI algorithms (aka, the “black box” problem). Many healthcare professionals and patients may not understand how AI reaches its conclusions, leading to a trust deficit. 
2. Bias: Because AI systems are data driven, they are only as good as the data they’re trained on. This raises concerns about bias. If the data is incomplete or unrepresentative, AI models may produce biased outcomes (more here), potentially exacerbating health disparities.
3. Privacy: The integration of AI into healthcare has raised ethical concerns, particularly around patient privacy and data security. AI systems often require access to sensitive health data, and this creates a need for strong data protection protocols. If not carefully regulated, there’s a risk of misuse or unauthorized access to this data. 
4. Human Participation in Decision Making: Some are afraid that AI might replace human judgment in critical healthcare decisions, diminishing the importance of the human element in patient care.
5. Regulations: The regulatory framework for AI in healthcare is still evolving, and it must strike a balance between innovation and safety. Regulators are working to establish guidelines that ensure AI technologies are safe and effective before they reach the market; however, these guidelines must also be flexible enough to accommodate rapid advancements in technology. 

Again, with great power comes great responsibility. As we enter a new phase of AI adoption, a major concern is ensuring accountability of this tool, delineating clear responsibilities if an AI system makes an error. We must define the roles and responsibilities of AI developers, healthcare providers, and regulators to ensure accountability in the event of an AI failure, in order to protect human rights.

We must play an active role in the development of AI in healthcare

As healthcare technologists and industry experts, we have a critical role to play in ensuring the responsible development of AI in healthcare. First, we must advocate for transparency in AI algorithms by pushing for explainable AI models that clearly show how they arrive at their decisions. Second, we must prioritize inclusivity in the data sets we use to train AI, ensuring the data represent diverse populations to reduce bias. Third, we must work closely with regulatory bodies to ensure AI technologies are thoroughly tested and meet safety standards before being deployed in healthcare settings. 

1upHealth is participating in the development of transparent, inclusive, and safe AI solutions by enabling secure, standardized health data exchange on the most advanced platform in the market. Not only does our 1up Platform provide the privacy and security needed to protect patient information, it also provides computable, high-quality data sets with the key insights needed to reduce bias and enhance patient care. We’re excited to continue along this journey. The future of AI in this industry is amazing! 

Closing thoughts

AI has the potential to revolutionize healthcare, but it must be approached with caution. The challenges of transparency, bias, ethics, and regulation are significant, but not insurmountable. By working together as healthcare technology experts, regulatory professionals, and health practitioners, we can take a patient-centric approach to creating AI systems that improve patient care while safeguarding privacy, security, and human dignity.