How to Deploy Generative AI in Healthcare without Sending Patient Data to External APIs?

Using Generative AI in healthcare will definitely simplify work for doctors, nurses, and staff in hospitals. It will help generate patient visit summaries, give answers to medical questions, and structure patient notes. At the same time, there is one problem that hospitals and clinics have to deal with – patient privacy.

While using popular and free AI algorithms available on the internet, all the text and other data you enter become available to some external servers. For healthcare, it is a very dangerous situation. The transmission of patient private medical information to any external APIs violates strict regulations such as HIPAA.

But how can hospitals take advantage of this advanced AI solution while protecting patient data? The solution is using AI right on the hospital’s server.

Why Public Cloud-based AI Is Dangerous for Hospitals?

In case physicians utilize regular cloud-based AI, all the messages they type will go via the Internet to servers of some big corporation.

• No Control: The hospital does not have control over the movement of this information and its security.
• Laws: There are laws which require that no one knows personal details about patients' illnesses and treatment.
• Leaks: In case if any third party server is attacked, then all confidential patient records may get into wrong hands.

For ensuring that a patient's information is safe, the hospital should find a way to keep everything inside of their own walls.

The Solution: Local Deployment

Hospitals have the ability to develop and deploy the AI model independently on the private computers of hospitals without any outsourcing of data to any third-party. The process is known as on-premises deployment.

Following are the steps which hospitals follow in order to do so:

1.  Choosing an Open Source AI Model

Nowadays, some very effective AI models developed by different organizations or research groups are available which are known as open source models. Hospitals have the option to select one such open source model and install it on the hardware of hospitals. As the code is public, the technical team at the hospital can verify and run it.

2.  Create Secure Local Computers

Artificial intelligence requires a lot of computational resources. The hospitals must purchase dedicated computers (servers) with powerful graphics processing units (GPUs). The servers will be housed within the premises of the hospital under the same protection as the electronic health records.

3.  Store Patient Data within the Hospital Premises

When a doctor requests information from an artificial intelligence, the information is requested within the hospital’s own local network. The information goes from the doctor’s computer to the hospital’s local AI server, then the AI provides the answer, which immediately goes back to the doctor’s computer. No data is sent anywhere outside the hospital premises.

Important Rules and Best Practices

Even if the AI system is kept local, there should be certain guidelines that must be followed by the hospitals which are as follows:

Name Removal: It is always better to remove the names, birth dates and telephone numbers before processing them in any tool. This will keep the vital information of this process safe.

Limited Access: The access to the AI tool should be restricted only to the authorized personnel.

Periodic Security Tests: The IT department of the hospital should conduct periodic security tests on the local servers in the same way as it does for the databases of other patients.

Benefits of Generative AI in Healthcare

Running AI locally is beyond simply protecting patient privacy. It also brings other great advantages which are given below:

• Increased Speeds: Since the information is not being sent over the Internet to a third-party server, responses come much faster.
• Offline Capability: In the case of an Internet failure at the hospital, the local AI would still be able to operate as long as there was power in the hospital.
• Customized Use: The hospital would be able to tailor the AI to their particular language of operation.

Conclusion

There is no need for hospitals to choose between technology and privacy. Healthcare facilities can have the advantages of modern technology while being safe from any risk through installation of open source AI systems in their own local server. Protection of patient confidentiality is the top priority of this digital revolution.