ZDNET’s key takeaways
- Athenahealth patients can consult Anthropic Claude.
- The partnership gives the AI access to sensitive health information.
- Athenahealth claims that the data cannot be used to train anthropic models.
A major US healthcare technology provider has just partnered with Anthropic to connect patient health records to Claude.
Athenahealth, a healthcare technology provider serving over 20% of the US population, is launching a Model Context Protocol (MCP) compliant server that connects to Anthropic’s Claude. The server, called AthenaPatient MCP, allows the AI model to gather information from health records and answer similar questions. The process is secure, according to Athenahealth, and requires patients to sign in with their account credentials.
AthenaPatient MCP is only available to Claude Pro and Claude Max users, which cost $20 and $100 per month, respectively. Not all Athenahealth patients will have their data shared with Claude, and not all Claude Pro and Claude Max users will have to opt in. Users must provide Claude with their authenticated Athenahealth credentials, can choose which health information Claude can access, and can revoke access at any time, according to the press release.
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Once authorized, Claude takes patient information such as lab results, vitals, medications, health conditions, immunizations, visit history, diagnostic reports, allergies, procedures and care plans into account when answering questions.
The AI Partnership does not provide medical advice, according to Sam Lambson, vice president of product management, data & ecosystem at Athenahealth, who responded to ZDNET in an email. Nor should it replace the professional judgment of a clinician or medical advice. “Patients should contact a qualified healthcare professional with questions about diagnosis, treatment or changes in their care,” Lambson said.
It appears that the AthenaPatient MCP tool is designed to help patients better understand information provided by healthcare professionals, rather than providing them with medical advice. So, one can ask an AthenaPatient MCP about their latest blood test results, such as “What was my last red blood cell count?” but users should not expect Claude to explain how an abnormally high or low number may affect them.
Not the first of its kind
Partnerships between Big Tech and Big Healthcare are not new. In fact, the collaboration between Athenahealth and Anthropic follows a larger trend in the health tech industry. Earlier this year, Microsoft partnered with Mayo Clinic to develop an AI model for healthcare; Boston Children’s Hospital has forged a partnership with OpenAI to develop an enterprise AI system for use across research, clinical and administrative teams, according to a press release.
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A growing number of Americans are consulting AI for medical advice. A recent survey by the Pew Research Center found that 34% of US adults have spoken to a chatbot for medical advice. This partnership makes the process a little more secure by authorizing patient account credentials before the model grants access to health records.
Health data is extremely valuable, and technology companies are increasingly interested in partnering with healthcare providers to access it. Much of the “AI could cure cancer” messaging we hear depends on these huge companies getting enough health data to train their AI models and link disease data to patient data. However, this is not to say that solving this complex problem is the motive behind the partnership between Athenahealth and Anthropic.
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A more reasonable explanation for such a partnership is that an AI that answers patient questions can eliminate some of the administrative work that doctors do between patient visits, such as answering questions about test results, giving Athenahealth doctors some time back.
Will partnerships like Anthropic and Athenahealth improve patient outcomes? That remains to be seen, but a recent survey by the Pew Research Center found that Americans are not so confident on the matter. The largest shares of respondents still prefer a human to supervise AI when it is used in a clinical context.