Work with HTM professionals
Providers should consult with and learn from HTM professionals about what their technologies actually do and the information they transmit. They should ask how secure these data exchanges are, and if they include any patient-identifiable information. They should also understand the purpose and function of data storage and backup locations, such as the cloud, and the risks and benefits associated with using them in their practices.

Together, clinicians and HTM professionals should define objectives for using each AI-based system; evaluate datasets for systems they are considering buying to ensure the data the technology was trained on aligns with the healthcare system’s actual patient population demographics and care needs; and plan for worst-case scenarios, such as alerting clinicians to errors made by a system or when results from the system are interpreted wrong by clinicians.

At the 2022 AAMI eXchange, ECRI’s Francisco Rodríguez-Campos said that providers should form multidisciplinary committees that include HTM professionals who can provide oversight and help develop policies for AI applications. They should be able to answer questions on how AI will affect the roles of employees, employee training, compliance requirements, and addressing cyberattacks.

He also recommended Incorporating vendor assessments and risk management into the procurement process, according to the AAMI report.

Processing data correctly
To protect data quality and patient privacy from cyber threats, AI manufacturers need to question how they acquire, clean, label and enrich data. This includes managing risks across the full life cycle of the equipment, and consulting providers more closely on what information is most likely to be targeted.

“We can’t just grab a bunch of medical records and feed them into a system. Just like any other type of raw material, there’s some processing we have to do before it goes into our product,” wrote Pat Baird, senior regulatory specialist at Philips and co-chair of AAMI’s Artificial Intelligence Committee.

It is also important to ensure data meets quality standards, as biased information can perpetuate unfair practices, and make AI solutions less effective at treating patient populations that they were not trained to address.

Fighting AI-based cyberattacks with AI
Cyberattacks are using AI more to breach hospital and healthcare networks with technology that’s so sophisticated, it can blend into the background and go unseen as it retrieves data or spreads viruses to corrupt systems, putting patient safety in danger and compromising data integrity, quality, and trust.

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