The authors' framework supports the release of de-identified and aggregated clinical data for research and development, as long as those receiving the data identify themselves and act as ethical data stewards. Individual patient consent would not be required, and patients would not necessarily be able to opt out of allowing their clinical data to be used for research or AI algorithm development—so long as their privacy is protected.
"When used in this manner," the article states, "clinical data are simply a conduit to viewing fundamental aspects of the human condition. It is not the data, but rather the underlying physical properties, phenomena and behaviors that they represent, that are of primary interest."
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According to the authors, it is in the best interest of future patients for researchers to be able to look "through" the data available in electronic medical records to develop insights into anatomy, physiology and disease processes in populations, as long as they are not looking "at" the identity of the individual patients.
The framework states that it is not ethical for clinical providers to sell clinical data for profit, especially under exclusive arrangements. Corporate entities could profit from AI algorithms developed from clinical data, provided they profit from the activities that they perform rather than from the data itself. In addition, provider organizations could share clinical data with industry partners who financially support their research, if the support is for research rather than for the data.
Safeguards to protect patient privacy include stripping the data of any identifying information.
"We strongly emphasize that protection of patient privacy is paramount. The data must be de-identified," Dr. Larson said. "In fact, those who receive the data must not make any attempts to re-identify patients through identifying technology."
Additionally, if a patient's name was unintentionally made visible—for instance, on a necklace seen on a CT scan—the receiver of the information would be required to notify the party sharing the data and to discard the data as directed.
"We extend the ethical obligations of provider organizations to all who interact with the data," Dr. Larson said.
Dr. Larson and his Stanford colleagues are putting the framework into the public domain for consideration by other individuals and parties, as they navigate the ethical questions surrounding AI and medical data-sharing.
