HIPAA-Compliant Alternatives to ChatGPT for Healthcare

Why small clinics search for ChatGPT alternatives

ChatGPT is the most widely adopted AI tool in the general population, and healthcare staff are no exception. The problem: the plans most staff use — Free and Plus — have no HIPAA coverage. When a medical assistant uses personal ChatGPT to draft a patient communication that includes the patient’s name, diagnosis, or treatment details, that is an unprotected disclosure of PHI, regardless of how common the behavior has become.

Searching for HIPAA-compliant alternatives is the right response. This guide covers what the OpenAI ecosystem itself offers for healthcare, what the major cloud AI platforms provide, and which purpose-built healthcare AI tools should be on a small clinic’s evaluation list.

What ChatGPT offers for healthcare — and what it does not

What standard plans cannot do

ChatGPT Free, Plus, and Team plans do not include a BAA. Using them with PHI creates an unprotected disclosure under HIPAA. This is the baseline fact that drives the need for alternatives.

Consumer account default behavior allows OpenAI to use prompt data for model training unless the user has enabled the training opt-out setting. Even with opt-out enabled, no legal protection exists because there is no BAA. Opt-out is a product setting; a BAA is a legal commitment.

What ChatGPT Enterprise offers

OpenAI offers a BAA through ChatGPT Enterprise and through qualifying API enterprise agreements. ChatGPT Enterprise:

• Requires direct engagement with OpenAI’s enterprise sales team
• Pricing is not published; it is negotiated based on organization size and usage
• Does not use enterprise prompt data for model training by default
• Provides administrative controls for user management and content policies
• Is appropriate for larger organizations with IT resources to manage an enterprise AI deployment

For small clinics without dedicated IT staff, ChatGPT Enterprise may not be the most practical path. The enterprise sales and implementation process is designed for organizations that can support it.

Alternative 1: Microsoft Azure OpenAI Service

What it is: Azure OpenAI Service makes OpenAI’s GPT-4 and related models available through Microsoft’s Azure cloud infrastructure. Access is through the Azure API, not through the chatgpt.com interface.

HIPAA posture: Azure OpenAI is covered under the Microsoft enterprise HIPAA BAA for qualifying Azure customers. Organizations with an existing Microsoft enterprise agreement can add Azure OpenAI to their HIPAA-covered workloads. Microsoft’s HIPAA BAA program covers a wide range of Azure services and is well-documented.

Practical considerations for small clinics:

• Best suited for organizations that already have a Microsoft enterprise relationship (Microsoft 365, Azure, Teams)
• Access is through the Azure API, which requires technical implementation — not a chatbot interface
• Organizations building healthcare applications on top of Azure OpenAI benefit from the unified Microsoft compliance framework
• For staff who want a ChatGPT-like interface, Azure OpenAI requires building or purchasing a front-end application on top of the API

Verification: Confirm that Azure OpenAI Service is included in your current Microsoft BAA scope. Microsoft’s compliance documentation lists which Azure services are in scope for the BAA — verify current status.

Alternative 2: AWS Bedrock

What it is: Amazon Web Services offers AWS Bedrock, a managed AI service that provides access to multiple AI models — Anthropic Claude (multiple versions), Amazon Titan, Meta Llama models, and others — through a unified AWS API.

HIPAA posture: AWS Bedrock is a HIPAA-eligible service under the AWS Business Associate Agreement. Organizations that have executed the AWS BAA (available to qualifying AWS customers) and that add Bedrock to their covered services can use AWS Bedrock for PHI workflows.

Practical considerations for small clinics:

• Similar to Azure OpenAI, AWS Bedrock access is through an API — it requires technical implementation
• Best suited for organizations that already have an AWS presence and an existing AWS BAA
• Provides model variety: if an organization wants to access Anthropic Claude or other models in a U.S.-based, AWS-managed environment, Bedrock is an option
• Healthcare organizations building custom AI applications on AWS can use Bedrock as the AI layer within their existing AWS compliance framework

Verification: Check the current AWS HIPAA-eligible services reference page for Bedrock’s current eligibility status, as AWS adds and updates the list of covered services over time.

Alternative 3: Anthropic Claude Enterprise API

What it is: Anthropic offers BAA coverage for enterprise API customers through the Claude API. This allows healthcare organizations building applications on the Claude API to do so under a covered business associate relationship with Anthropic.

HIPAA posture: Anthropic offers a BAA for qualifying enterprise API customers. Enterprise prompt data is not used for model training by default. Verify current terms with Anthropic’s enterprise team.

Practical considerations for small clinics:

• Best suited for organizations building or evaluating custom healthcare applications on the Claude API
• For healthcare developers who prefer Claude’s model characteristics, the enterprise API provides a direct BAA path without routing through a cloud intermediary
• Consumer Claude.ai plans (Free, Pro) have no BAA and cannot be used with PHI — the BAA is available only through the enterprise API arrangement

Verification: Contact Anthropic’s enterprise sales team to confirm current BAA availability and the scope of covered services. See is Claude HIPAA compliant and is Anthropic HIPAA compliant for detailed analysis.

Alternative 4: Purpose-built healthcare AI scribes

For the most common use case that drives clinics to seek ChatGPT alternatives — documentation support and clinical note generation — purpose-built healthcare AI scribes are a more appropriate solution than enterprise general-purpose LLMs.

Why scribes rather than general LLMs for documentation

Healthcare AI scribes are designed for clinical workflows:

• They integrate directly with EHR platforms, reducing the copy-paste workflow
• They are trained on clinical language and can generate properly structured notes (SOAP, HPI, A&P)
• Their HIPAA compliance infrastructure is already built for the clinical use case — they are not an enterprise IT deployment project
• They have active BAA programs designed for healthcare providers, not enterprise IT departments

Nabla

Nabla is an ambient AI scribe that listens to clinical encounters and generates structured documentation. It integrates with major EHRs. Nabla executes BAAs and is designed for HIPAA compliance in the clinical encounter workflow. Pricing is per-provider subscription — accessible for small independent practices.

Abridge

Abridge captures patient-provider conversations and generates clinical notes. Abridge has established healthcare enterprise relationships and executes BAAs. Current deployments tend toward larger systems, but small clinic availability should be confirmed directly.

Suki AI

Suki AI is a voice AI assistant for physicians that handles documentation tasks including note generation, clinical queries, and coding suggestions. Suki executes BAAs with covered entities and integrates with major EHR systems.

DeepScribe

DeepScribe is an ambient AI medical scribe that creates clinical notes from encounter audio. It integrates with multiple EHR systems and executes BAAs. Designed for specialty and primary care practices.

What to do about staff using consumer ChatGPT now

The immediate operational problem for most clinics is not which enterprise AI platform to adopt — it is that staff members are already using consumer ChatGPT, Perplexity, or similar tools for work tasks, including tasks that involve patient information.

Addressing this requires:

1. An AI use policy — a written policy that names approved tools, prohibited tools (including standard ChatGPT, Perplexity, DeepSeek), and the process for requesting new tool approvals
2. Workforce training — staff must understand why consumer AI tools are prohibited for PHI, not just that they are prohibited
3. Incident review — assess whether existing use of prohibited tools has created reportable incidents
4. An approved alternative — staff who are using ChatGPT for legitimate work tasks need an approved alternative; prohibiting a tool without providing a replacement creates pressure to violate the policy

The HIPAA AI use policy template provides a starting framework for the policy. For the broader AI tool evaluation framework, see PHI in AI tools and best HIPAA-compliant AI tools for clinics.

Compliance program management alongside AI tools

Adopting HIPAA-compliant AI tools is a vendor decision. Building the compliance program to manage those tools — tracking BAAs, training staff, documenting incidents, maintaining the AI use policy — is an organizational capability that requires dedicated infrastructure.