AI for Healthcare: Hathr AI is your HIPAA Compliant LLM
Hathr AI speeds up Healthcare Teams by 10x or more –
Learn how Healthcare Teams are using Hathr AI to accelerate or automate their work
Keep patient data secure by using Hathr AI's HIPAA compliant AI tool
AI in healthcare is changing how clinicians and administrative teams work. Summarize clinical notes, analyze previous visits, and get insights into a patient’s health and previous care. Don’t forget to ask Hathr AI to provide a summarization of care and suggest the associated insurance billing codes for care.
Hathr AI speeds up healthcare and admin tasks by >10x
Summarize clinical notes and patient logs
Use Hathr AI to move faster and protect sensitive patient data. You can now start to generate healthcare insights through Hathr’s analysis & summarization capabilities that otherwise would be borderline inaccessible. AI in healthcare is changing the game, and Hathr AI is leading the way with our flexible
Securely analyze medical data
Use Hathr to analyze one patient’s medical records, or data across thousands of patients. There’s no dataset too large, and Hathr can help to improve your quality of patient care and medical research.
Provide options and recommendations
Upload complicated information and analyze the data for suggestions to complex issues, and translate those into billable codes to help your team move faster and patients get the care they need.
Other AI tools can expose sensitive information
This risks the exposure of patient data and classified information to the public
Other AI tools reuse your data to train their models, and this data can be accessed by other users – which is not HIPAA Compliant or Private. PHI, PII, or Confidential Information has to be protected.
Other Commercial AI tools like ChatGPT are not compliant with HIPAA or NIST 800-171, so they don’t meet regulatory policies.
“GPT or platforms powered by GPT leak your proprietary information and reuse your data to make their platform better for free.”
– James Vincent, The Verge
The power of tools like Anthopic's Claude AI + the privacy of Hathr
When you’re using AI in healthcare, you need to give your team quality and safe AI options
Comparing Leading AI Models for Clinical Text Processing: An Observational Study
“Claude 3.5 Sonnet excelled in providing structured responses, clearly categorizing information and often separating positive and negative findings. This approach could be particularly useful for quick information retrieval in clinical settings. Moreover, Claude 3.5 Sonnet’s exceptional context window of 200,000 tokens allows it to process and analyze much larger volumes of clinical text in a single interaction, making it particularly suitable for handling comprehensive medical records or multiple documents simultaneously.” – Mohit Kataria, Manthan Research and Analytics
Hathr is making an impact in the healthcare space
Research hundreds of pages patient records in minutes.
My patient had a complex medical history, and I needed to be able to find a specific record quickly during our visit. Hathr AI found the visit and created a patient summary in seconds
– Nicole J.
MD
Hathr is a game changer.
Our team can now go through a document in seconds and start responding to sections of the proposal. It’s all private so I’m not worried that GPT will just feed all my competitors what made us win the bid.
– Paul D.
Government Contracting
I don’t have to worry about leaking data.
I uploaded all the documents from my technical team and then asked Hathr to create an outline and draft sections based on the technical docs. Since it’s all private, I don’t have to worry about leaking my company’s proprietary data when I upload a document.
– Ryan K.
Technical Writing
Use Hathr in whatever way is easiest for you
- Sign up for an individual account
- Get group access for your organization
- License Hathr to run on your own infrastructure
- Use our API to built compliant AI tools
Still curious about AI in Healthcare?
Keep reading, or reach out to our team to learn more:
AI in Healthcare: Transforming Healthcare with HIPAA-Compliant AI
AI in healthcare is starting to radically shift the healthcare landscape. AI in healthcare is starting a technological revolution, and one of the most exciting innovations is the integration of AI into clinical and administrative workflows. AI, particularly in the form of generative AI and large language models (LLMs), is offering new possibilities for improving patient care, streamlining administrative processes, and enhancing decision-making across healthcare systems.
However, with this promise comes a critical responsibility: ensuring that AI applications comply with healthcare’s most stringent regulations, especially the Health Insurance Portability and Accountability Act (HIPAA). HIPAA-compliant AI is not just a necessity—it’s the foundation for safely and securely incorporating AI into healthcare.
Keep reading about why HIPAA compliance is essential for AI in healthcare, the difference between a general-purpose LLM and a HIPAA-compliant LLM, and how Hathr AI is leading the charge in ensuring AI can safely and effectively transform healthcare.
Why HIPAA Compliance is Crucial in AI for Healthcare
The healthcare industry handles some of the most sensitive and protected data —Protected Health Information (PHI) and Personally Identifiable Information (PII). Under HIPAA, healthcare providers, insurers, and their business associates are required to protect the privacy and security of this data, including any applications or tools that process or access it.
AI in healthcare needs to be able to store and handle PHI and PII, and AI tools must meet these regulatory standards to prevent unauthorized access, ensure data integrity, and maintain the confidentiality of patient information. Failure to comply with HIPAA can result in severe consequences, including hefty fines, loss of patient trust, and legal action.
Key Aspects of HIPAA Compliance for AI in Healthcare
- Data Encryption: Any AI tool used in healthcare must encrypt patient data both in transit (when data is being sent across networks) and at rest (when data is stored on servers). This ensures that unauthorized individuals cannot access or tamper with sensitive information. AI in healthcare also needs to be able to use private connections to make sure that data isn’t transferred over the public internet.
- Secure Data Storage: AI in healthcare should use HIPAA-compliant systems to store data in secure, isolated environments that follow best practices for data protection. This includes using specialized cloud platforms like AWS GovCloud, which are specifically designed for sensitive data and meet rigorous federal security standards.
- Access Controls: Role-based access control (RBAC) is a critical component of HIPAA compliance. AI systems must restrict access to PHI based on the user’s role and authorization level, ensuring that only the right individuals (doctors, nurses, administrators) can access the data necessary for their work.
- Audit Trails: HIPAA mandates the ability to monitor and record access to sensitive health data for all data handling, especially with systems that integrate AI in healthcare. AI systems must provide an auditable record of all data access and processing activities, allowing healthcare organizations to quickly detect any potential breaches or unauthorized access. Making sure to audit how your data is transmitted and stored is critical
What is a HIPAA Compliant LLM?
A Large Language Model (LLM) like GPT, Claude, Gemini, or similar generative AI models can provide powerful capabilities for natural language processing, such as summarizing text, answering questions, and generating human-like text. However, a standard LLM, such as the one powering many public chatbots, is not HIPAA-compliant. These models are generally not built with the necessary security features to protect PHI, which is a major concern when handling healthcare data.
Why Regular LLMs Are Not HIPAA-Compliant
- Data Handling: Non-compliant LLMs may store conversations or user inputs in ways that do not align with HIPAA’s privacy standards. In some cases, AI models may retain sensitive data indefinitely, or the data could be used for training purposes, violating patient confidentiality.
- Lack of Encryption: Public LLMs often do not offer end-to-end encryption, meaning that data could potentially be intercepted during transmission or accessed by unauthorized parties.
- Inadequate Access Controls: Regular LLMs don’t have the robust role-based access controls necessary to ensure that only authorized personnel can access or use patient data.
- Non-compliant Infrastructure: Many general-purpose AI models are not hosted in a secure, HIPAA-compliant environment. They may be run on servers that are not designed to meet the regulatory requirements for healthcare data.
In contrast, HIPAA-compliant LLMs like Hathr AI are specifically engineered to address these concerns, ensuring that every aspect of the model’s architecture and data handling complies with HIPAA regulations.
Key Features of a HIPAA-Compliant LLM
- End-to-End Encryption: From the moment data enters the system to its final storage, everything is encrypted to ensure that PHI is never exposed to unauthorized individuals.
- Secure Data Storage: All data used by the LLM is stored in HIPAA-compliant environments, such as AWS GovCloud, which are purpose-built to meet federal security and privacy standards.
- Compliance Monitoring and Reporting: A HIPAA-compliant LLM includes features for ongoing compliance monitoring, ensuring that the system continuously adheres to HIPAA guidelines and provides real-time alerts for any security issues.
- Role-Based Access: Access to sensitive data is tightly controlled, ensuring that only authorized users can access or process PHI. This reduces the risk of data breaches and ensures compliance with privacy laws.
How Hathr AI Revolutionizes Healthcare Operations
1. Streamlining Clinical Workflows
AI in Healthcare has the opportunity to help professionals that are often overwhelmed with administrative tasks, leading to burnout and reduced focus on patient care. Hathr AI integrates advanced language models into clinical workflows to save time, reduce administrative burden, and enhance productivity.
- Example Use Case: Mental healthcare providers can use Hathr AI to automatically transcribe and summarize patient sessions in real time, significantly reducing the time spent on documentation and allowing clinicians to focus more on patient care.
2. Enhancing Clinical Decision Support
AI-powered tools can provide clinicians with timely, evidence-based recommendations to support decision-making. Hathr AI pulls data from various uploaded sources (EHRs, lab results, treatment guidelines) to provide personalized suggestions for patient care.
- Example Use Case: A psychiatrist can ask Hathr AI for guidance on treatment options based on the latest research and the patient’s specific medical history, improving decision-making and patient outcomes.
3. Improving Care Coordination
Patients often see multiple healthcare providers, making it difficult to coordinate care. Hathr AI can ingest data from different sources (primary care physicians, specialists, therapists) and a Doctor can query the information to create a holistic view of the patient’s health without having to take hours poring through medical records.
- Example Use Case: For a patient with both physical and mental health needs, Hathr AI can ingest documentation from a psychiatrist, therapist, and primary care doctor, and query all the information for relevant results and ways ahead for patients.
Hathr AI’s Administrative Superpowers
Automated Billing and Claims Management
Billing errors and claim denials are a significant burden on healthcare providers. Hathr AI can automate billing processes, verify coding, and flagg potential errors before submission to insurers, significantly reducing errors and speeding up reimbursement.
How It Works: Hathr AI uses its corpus of knowledge and uploaded documentation to analyze patient records and automatically suggest accurate billing codes, improving accuracy and ensuring that claims comply with regulations.
Why Choose Hathr AI?
Security and Compliance First
Unlike generic AI solutions, Hathr AI was built from the ground up to be the safe option for AI in healthcare with HIPAA compliance at its core. Every feature and function is designed to protect patient data while delivering exceptional AI-powered healthcare solutions. Hathr AI’s deployment in secure, FedRAMP-certified environments ensures the highest levels of security, meeting both HIPAA and other federal regulations.
For AI in healthcare, Hathr AI is your teammate to provide the best flexibility and capability to help your organization streamline operations and protect patients.
Customization for Healthcare Needs
Hathr AI is built to amplify teams across healthcare. Hathr AI can be customized for specific team needs, so that AI in healthcare is providing the best outcomes for patients and providers. Hathr AI works with healthcare organizations to identify workflows, and customize AI tools to automate or augment teams to make processes more efficient and painless. Whether that’s improving patient care, reducing administrative burdens, or enhancing decision support. Hathr AI is your team for AI in healthcare.
The Future of AI in Healthcare: Customizable and secure AI with Hathr AI
The future of AI in healthcare hinges on ensuring that AI tools are designed with security and privacy at their core. Hathr AI is leading the way in creating HIPAA-compliant LLM solutions that help healthcare organizations unlock the full potential of AI while keeping patient data safe and secure.
Whether you’re a mental health provider looking to streamline your operations or a large healthcare system aiming to enhance patient outcomes, Hathr AI is the trusted partner to help your team navigate the future of AI in healthcare with confidence.