MDCalc has officially introduced CrossCover to help clinicians navigate medical artificial intelligence chatbots securely. The platform operates differently from rivals like Epic, Abridge, and OpenEvidence, which routinely incorporate extensive patient, payer, and provider datasets. Rather than requiring clinicians to provide national identification numbers or navigate complex privacy frameworks, CrossCover strips out protected health information entirely from clinical queries. This privacy-first design ensures sensitive data is never exposed while clinicians seek automated medical guidance.
Key points
The platform avoids requiring clinicians to submit national identification numbers for sy…: The platform avoids requiring clinicians to submit national identification numbers for system use.
MDCalc is differentiating its tool from competitors that heavily integrate expansive heal…: MDCalc is differentiating its tool from competitors that heavily integrate expansive healthcare data.
Removing protected health information is intended to build physician trust and accelerate…: Removing protected health information is intended to build physician trust and accelerate technology adoption.
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MDCalc, a medical reference tool site, Wednesday announced the launch of CrossCover, which the company said is meant to help clinicians trust the answers of medical artificial intelligence chatbots while preserving patient and provider privacy.
Graham Walker, head of AI at MDCalc, said the company sees the tool as an accelerator for clinical generative AI. “We can take away some of the challenges and risks and problems with the technology so that physicians can feel more confident in using it,” he said.
CrossCover takes an approach that contradicts that of medical AI tools from OpenEvidence, Abridge, and electronic health record company Epic, which are trying to incorporate an ever-widening repertoire of patient, provider, and payer information into their recommendations. Rather than requiring clinicians to register with their national identification numbers or trying to mitigate risk by brokering privacy agreements that allow clinicians to enter protected patient health information, MDCalc’s tool focuses on stripping out those types of information from clinicians’ queries.
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