How Guardoc transforms medical document processing with Amazon Nova models

<p>Every day, nurses and care teams make critical decisions based on clinical documentation that is often fragmented, inconsistent, and prone to errors. Incomplete or inaccurate records increase cognitive load, introduce clinical risk, and create compliance challenges in an already demanding environment. Medical documentation must serve both patient outcomes and regulatory standards, yet too often it falls short on both fronts.</p> <p><a href="https://www.guardoc.health/" target="_blank" rel="noopener">Guardoc Health</a>’s mission is to unlock the full value of medical data by facilitating accurate, complete, and compliance-aligned clinical documentation, empowering nurses and care teams to deliver safer and higher-quality care. In this post, we explore how Guardoc Health uses the <a href="https://www.aboutamazon.com/news/aws/amazon-nova-artificial-intelligence-bedrock-aws" target="_blank" rel="noopener">Amazon Nova</a> family of models, available through <a href="https://aws.amazon.com/bedrock/" target="_blank" rel="noopener">Amazon Bedrock</a>, to transform clinical documentation in long-term care.</p> <p>With Amazon Nova models, Guardoc Health helps skilled nursing facilities and assisted living centers extract, classify, and act on complex documents faster and more accurately than manual review. This approach helps healthcare organizations reduce the hundreds of millions of dollars spent annually on manual document processing across the United States. Guardoc reports a 46 percent reduction in documentation errors, 70 percent fewer audit fines, and over $400K in annual return on investment (ROI) for a single facility.</p> <h2 id="medical-documents-dont-follow-rules">Medical documents don’t follow rules</h2> <p>Medical records arrive in every format imaginable. In a single day, a healthcare organization might process:</p> <ul> <li>Multi-page PDFs with handwritten physician annotations alongside printed text.</li> <li>Prior authorization forms where checkbox states determine coverage decisions. A prior authorization form is a document the doctor or pharmacist fills out so a health-insurance plan can approve certain medical services, procedures, or medications.</li> <li>Medication lists embedded in tables, free text, or scanned images.</li> <li>Patient intake forms combining typed fields, handwriting, and rubber stamps.</li> </ul> <p>According to research published in BMJ Quality and Safety <a href="https://qualitysafety.bmj.com/content/23/9/727" target="_blank" rel="noopener">¹</a>, diagnostic errors affect approximately 12 million U.S. adults each year in outpatient care, with information-handling failures identified as a contributing factor. Guardoc Health was built to address this variable. For Guardoc Health, the challenge is scale combined with precision. On peak days, they process more than 1 million documents. At that volume, even a 1 percent error rate in condition detection generates thousands of incorrect records daily, each one a potential patient safety risk or compliance liability.</p> <p>Achieving this required solving three of the hardest challenges in clinical document processing: detecting special medical conditions from patient records with high recall, reliably interpreting PDF checkboxes across dozens of form types, and accurately extracting information from documents that mix formats within a single page.</p> <h2 id="the-solution-amazon-nova-models-on-amazon-bedrock">The solution: Amazon Nova models on Amazon Bedrock</h2> <p>Guardoc Health built its pipeline on the Amazon Nova family of models and Amazon Bedrock, combining several AWS services to handle each stage of document processing. The following sections describe how each part works.</p> <h3 id="medical-condition-classification-with-rag">Medical condition classification with RAG</h3> <p>Guardoc Health uses Retrieval Augmented Generation (RAG) to identify medical conditions from patient records. RAG is a technique in wh