March 4, 2021

Healthcare AI News

All About Artificial Intelligence in Healthcare

Developing AI in Healthcare

Top Legal Considerations While Developing Artificial Intelligence in Healthcare

As the use of AI increases, so will the list of legal considerations that have to be dealt with. While that may seem tedious, it is the only way AI can flourish in healthcare.

While AI has a lot of advantages to its name, it comes with its fair share of legal challenges. Listed below are some of the top legal issues that healthcare companies should consider while developing AI tools.

1. Statutory, Regulatory and Common Law Requirements

There are several statutory, regulatory and common law requirements that may be implicated for both healthcare providers and developers when considering AI in the healthcare domain. Based on the function the AI tool is discharging, healthcare providers or an AI developer might have to apply for licensure, permits and other registrations in compliance with state and federal laws. For instance, AI may require FDA approval to make a diagnosis without a healthcare professional’s review. Furthermore, as the functionality of AI expands, several questions about regulations may be raised. How will the services be regulated? Will the provision of such services be considered the unlicensed practice of medicine or in violation of corporate practice of medicine prohibitions? These considerations must be answered before AI is implemented in a healthcare organization.

2. Ethical Considerations

The use of AI in healthcare raises many ethical questions relating to accountability, transparency and consent because decisions in healthcare are not made exclusively by humans anymore. For example, a patient may fail to

understand their diagnoses made by a deep-learning system because the physicians themselves often don’t understand the basis of the diagnosis made by AI. Furthermore, AI is not immune to algorithmic biases, which could sometimes lead to incorrect diagnosis. This makes it difficult to pin accountability when errors in diagnosis occur while using AI.

3. Reimbursement Issues

AI has the ability to affect every aspect of revenue cycle management. The main concern here is that errors could occur when requesting reimbursement through AI. In the inevitable event that an error occurs, it may be unclear as to who is ultimately responsible unless it is clearly stipulated in a contract. That takes us to the next point…

4. Contractual Exposure

For the smooth and efficient use of AI, it is extremely crucial to have clearly articulated contracts governing the sale and use of the technology. Some important contractual terms involve insurance, expectations regarding services, representations and warranties, indemnification, and changes in law, among other things.

5. Torts and Private Causes of Action

Under theories of strict liability, a developer will be held liable in case the AI tool has design defects or is inadequately planned or unreasonably hazardous to consumers. As AI evolves, tort theories could also begin to hold the AI itself liable. As a result, the developer and provider will likely have exposure to liability (professional or product liability depends on the functionality of AI) associated with AI.

6. Privacy and Security Risks

The development and use of AI in healthcare raises unique challenges to companies that have ongoing obligations to safeguard protected health information and other sensitive information. AI requires huge amounts of data to work effectively and as a result, its usage may implicate the Health Insurance Portability and Accountability Act (HIPAA) and state-level privacy and security laws with respect to such data may need to be de-identified. Additionally, patient authorization may be needed before the disclosure of the data via AI or to the AI.

7. Intellectual Property Considerations

It is of particular importance for AI developers to preserve and protect the intellectual property rights that they may be able to assert over their developments (patent rights, trademark rights, etc.) and for users of AI to understand the rights they have to use the AI they have licensed. It also is important to consider carefully who owns the data that the AI uses to “learn” and the liability associated with such ownership.

8. Compliance Program Implications

When new technology such as AI is introduced, compliance programs should also be updated accordingly. It is also extremely important that the workforce using AI is properly trained to operate the technology. Similar to a traditional compliance plan, continual monitoring and evaluation should take place and policies should be updated to keep up with ever-evolving AI technologies.

As the use of AI increases, so will the list of legal considerations that have to be dealt with. While that may seem tedious, it is the only way AI can flourish in healthcare.