How manufacturers of artificial intelligence can protect themselves against future negligence claims | Insights

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Innovative medical devices have changed the healthcare landscape and will continue to dramatically improve patient care. Nonetheless, the proliferation of such devices will inevitably lead to increased litigation over their alleged failures. All companies developing health technology must therefore consider measures to protect themselves against potential claims. You can find out more about lawsuit loans from this imp source.

Any litigation that arises from medical technology using AI – especially AI used as part of a diagnosis or intervention – is likely to be complicated. Medtech often involves a complex chain of actions involving a number of different parties, from medical device manufacturers to programmers to doctors. If the AI ​​is blamed for a patient’s misdiagnosis, it can be attributed to a series of interrelated events rather than a single error. In such circumstances, individuals who have suffered personal injury can appeal against anyone involved in their care.

This could possibly include the manufacturer who developed and marketed the AI, but also the doctor who enters data into the AI ​​or interprets data that comes from the AI. It could also include suing the local doctor to try to prevent deportation in federal court and starting a lawsuit in what may be a more balanced forum.

To this complexity comes the so-called “black box” challenge with regard to the AI ​​itself. Even if it is possible to know what data was entered into the AI ​​and what the final output data of the AI ​​was, the exact steps of the algorithm for the Reaching the issue decision cannot always be fully understood. You can’t always ask the AI ​​to explain its results in the same way that you can ask a doctor. In certain circumstances it may be possible to trace the parameters back, but it can be challenging to determine the basis for the alleged error or the ambiguity of the result.

However, there are steps those developing AI-based medical technology can take to minimize the risk. First, stay up to date on specific government guidance on AI and, if applicable, especially if your device is being used for diagnostics, work with regulators to obtain appropriate approvals and submissions related to your device. An essential threshold question here will be whether the software in question is even regulated by the FDA or is considered a safe haven.

Second, to support and justify the appropriate role of the treating physician’s medical judgment in patient care. Develop the AI ​​in an explainable way, provide documentation or training to users on how the AI ​​works, and consider the role of doctors in making your own medical assessment rather than relying solely on a recommendation from the AI. Communicate in a way that makes it clear that all final decisions about patient care must be with the patient’s attending physician.

Third, find and use advice on how to minimize security risks posed by AI. Patient data require increased attention for data protection. For example, if a hacked digital health product injures a patient, product liability may depend on the ability of the medical device manufacturer or software designer to develop a system immunized against cybersecurity attacks and the extent to which such a deficiency is reasonably foreseeable, given the public awareness of Cyber ​​security issues.

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While no use of AI is risk-free, a manufacturer that considers and mitigates risk in the earliest stages is best positioned to defend itself with minimal impact on its business.


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